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Liu, Yi. "Movement detection in outdoor scenes for traffic monitoring". Thesis, University of Ottawa (Canada), 2004. http://hdl.handle.net/10393/26698.
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One important application of image processing and computer vision is traffic monitoring and control. In this thesis, a system for detection of moving vehicles approaching an intersection from a sequence of color images acquired by a stationary camera in the context of traffic light control systems is presented. As the system is dedicated to outdoor applications, efficient and robust vehicle detection under various weather and illumination conditions is examined. To deal with these ever changing conditions, vehicle detection relies on motion segmentation and on an original algorithm using color mapping to achieve feature space segmentation. Experimental results on real outdoor sequences of images demonstrate the system's robustness under various environmental conditions.
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Zhu, Shiping. "Robust detection of object movement by a mobile camera system". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq28696.pdf.
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Blanchard, Jonathan Mark. "Collision avoidance : a biologically inspired neural network for the detection of approaching objects". Thesis, University of Newcastle upon Tyne, 1998. http://hdl.handle.net/10443/3590.
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The frequently studied lobula giant movement detector (LGMD) system of the locust responds most strongly to approaching objects. This thesis describes simulations which were designed with the ultimate aim of constructing a comprehensive model of the neural circuitry showing the effects of individual neurons on the overall responses of the system. The Rind and Bramwell neural network model of the LGMD was studied using new stimuli which revealed that the responses of the model are dependent on the shape of the stimulus. A modification of the model removes this dependence and allows the model to respond to more complex stimuli. Two models of a locust photoreceptor were developed with the aim of producing a detailed model of a light-adapting photoreceptor which could be used to study the responses of the LGMD to natural scenes. The first model, an electrical model of the cell membrane which describes the principal ionic conductances, was found to be overly complex for use in large scale simulations. However, the model was used to calculate from the photoreceptor's impulse response the average conductance change produced by individual photons. The second photoreceptor model, which is suitable for large scale simulations, uses two leaky integrators to mimic the effects of light adaptation on the photoreceptor's response. An electrical model of the lamina region of the optic lobe allowed the proposal that inhibition in the lamina is produced by electrical presynaptic inhibition to be studied, along with the possible effects of this inhibition on the visual input to the LGMD. The responses of the model correspond well with those measured from the LMCs of locusts and other insects, and their implications for the LGMD system are discussed.
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Feng, Dehua. "Determining Intersection Turning Movements with Detection Errors". University of Akron / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=akron1512746695445707.
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Jalloul, Nahed. "Development of a system of acquisition and movement analysis : application on Parkinson's disease". Thesis, Rennes 1, 2016. http://www.theses.fr/2016REN1S096/document.
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Le travail présenté dans ce mémoire porte sur le développement d'un système de surveillance ambulatoire pour la détection de la dyskinésie induite par la Levodopa (LID) chez les patients de la maladie de Parkinson (PD). Le système est composé d’unités de mesure inertielle (IMUs) qui recueillent des signaux de mouvement chez des sujets sains et des patients parkinsoniens. Des méthodes différentes sont évaluées pour la détection de LID avec et sans classification des activités. Les données recueillies auprès des sujets sains sont utilisées pour concevoir un classificateur d'activité fiable. Par la suite, un algorithme qui effectue la classification des activités et la détection de la dyskinésie sur les données recueillies auprès de des patients parkinsoniens est proposé. Une nouvelle approche basée sur l'analyse de réseau complexe est également explorée et présente des résultats intéressants. Les méthodes de traitement développées ont été intégrées dans une plateforme complète d’analyse nommée PARADYSEThe work presented in this thesis is concerned with the development of an ambulatory monitoring system for the detection of Levodopa Induced Dyskinesia (LID) in Parkinson’s disease (PD) patients. The system is composed of Inertial Measurement Units (IMUs) that collect movement signals from healthy individuals and PD patients. Different methods are evaluated which consist of LID detection with and without activity classification. Data collected from healthy individuals is used to design a reliable activity classifier. Following that, an algorithm that performs activity classification and dyskinesia detection on data collected from PD patients is tested. A new approach based on complex network analysis is also explored and presents interesting results. The evaluated analysis methods are incorporated into a platform PARADYSE in order to further advance the system’s capabilities
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Uppströmer, Viktor y Henning Råberg. "Detecting Lateral Movement in Microsoft Active Directory Log Files : A supervised machine learning approach". Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18337.
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Cyberattacker utgör ett stort hot för dagens företag och organisationer, med engenomsnittlig kostnad för ett intrång på ca 3,86 miljoner USD. För att minimera kostnaden av ett intrång är det viktigt att detektera intrånget i ett så tidigt stadium som möjligt. Avancerande långvariga hot (APT) är en sofistikerad cyberattack som har en lång närvaro i offrets nätverk. Efter attackerarens första intrång kommer fokuset av attacken skifta till att få kontroll över så många enheter som möjligt på nätverket. Detta steg kallas för lateral rörelse och är ett av de mest kritiska stegen i en APT. Syftet med denna uppsats är att undersöka hur och hur väl lateral rörelse kan upptäckas med hjälp av en maskininlärningsmetod. I undersökningen jämförs och utvärderas fem maskininlärningsalgoritmer med upprepad korsvalidering följt av statistisk testning för att bestämma vilken av algoritmerna som är bäst. Undersökningen konkluderar även vilka attributer i det undersökta datasetet som är väsentliga för att detektera laterala rörelser. Datasetet kommer från en Active Directory domänkontrollant där datasetets attributer är skapade av korrelerade loggar med hjälp av datornamn, IP-adress och användarnamn. Datasetet består av en syntetisk, samt, en verklig del vilket skapar ett semi-syntetiskt dataset som innehåller ett multiklass klassifierings problem. Experimentet konkluderar att all fem algoritmer klassificerar rätt med en pricksäkerhet (accuracy) på 0.998. Algoritmen RF presterar med den högsta f-measure (0.88) samt recall (0.858), SVM är bäst gällande precision (0.972) och DT har denlägsta inlärningstiden (1237ms). Baserat på resultaten indikerar undersökningenatt algoritmerna RF, SVM och DT presterar bäst i olika scenarier. Till exempel kan SVM användas om en låg mängd falsk positiva larm är viktigt. Om en balanserad prestation av de olika prestanda mätningarna är viktigast ska RF användas. Undersökningen konkluderar även att en stor mängd utav de undersökta attributerna av datasetet kan bortses i framtida experiment, då det inte påverkade prestandan på någon av algoritmerna.Cyber attacks raise a high threat for companies and organisations worldwide. With the cost of a data breach reaching $3.86million on average, the demand is high fora rapid solution to detect cyber attacks as early as possible. Advanced persistent threats (APT) are sophisticated cyber attacks which have long persistence inside the network. During an APT, the attacker will spread its foothold over the network. This stage, which is one of the most critical steps in an APT, is called lateral movement. The purpose of the thesis is to investigate lateral movement detection with a machine learning approach. Five machine learning algorithms are compared using repeated cross-validation followed statistical testing to determine the best performing algorithm and feature importance. Features used for learning the classifiers are extracted from Active Directory log entries that relate to each other, with a similar workstation, IP, or account name. These features are the basis of a semi-synthetic dataset, which consists of a multiclass classification problem. The experiment concludes that all five algorithms perform with an accuracy of 0.998. RF displays the highest f1-score (0.88) and recall (0.858), SVM performs the best with the performance metric precision (0.972), and DT has the lowest computational cost (1237ms). Based on these results, the thesis concludes that the algorithms RF, SVM, and DT perform best in different scenarios. For instance, SVM should be used if a low amount of false positives is favoured. If the general and balanced performance of multiple metrics is preferred, then RF will perform best. The results also conclude that a significant amount of the examined features can be disregarded in future experiments, as they do not impact the performance of either classifier.
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Yekhshatyan, Lora. "Detecting distraction and degraded driver performance with visual behavior metrics". Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/910.
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Driver distraction contributes to approximately 43% of motor-vehicle crashes and 27% of near-crashes. Rapidly developing in-vehicle technology and electronic devices place additional demands on drivers, which might lead to distraction and diminished capacity to perform driving tasks. This situation threatens safe driving. Technology that can detect and mitigate distraction by alerting drivers could play a central role in maintaining safety. Correctly identifying driver distraction in real time is a critical challenge in developing distraction mitigation systems, and this function has not been well developed. Moreover, the greatest benefit may be from real-time distraction detection in advance of dangerous breakdowns in driver performance.
Based on driver performance, two types of distraction - visual and cognitive - are identified. These types of distraction have very different effects on visual behavior and driving performance; therefore, they require different algorithms for detection. Distraction detection algorithms typically rely on either eye measures or driver performance measures because the effect of distraction on the coordination of measures has not been established. Combining both eye glance and vehicle data could enhance the ability of algorithms to detect and differentiate visual and cognitive distraction.
The goal of this research is to examine whether poor coordination between visual behavior and vehicle control can identify diminished attention to driving in advance of breakdowns in lane keeping. The primary hypothesis of this dissertation is that detection of changes in eye-steering relationship caused by distraction could provide a prospective indication of vehicle state changes. Three specific aims are pursued to test this hypothesis. The first aim examines the effect of distracting activity on eye and steering movements to assess the degree to which the correlation parameters are indicative of distraction. The second aim applies a control-theoretic system identification approach to the eye movement and steering data to distinguish between distracted and non-distracted conditions. The third aim examines whether changes of eye-steering coordination associated with distraction provide a prospective indication of breakdowns in driver performance, i.e., lane departures.
Together, the three aims show how that a combination of visual and steering behavior, i.e., eye-steering model, can differentiate between non-distracted and distracted state. This model revealed sensitivity to distraction associated with off-road glances. The models derived for different drivers have similar structure and fit to data from other drivers reasonably well. In addition, the differences in model order and model coefficients indicate the variability in driving behavior: some people generate more complex behavior than others. As was expected, eye-steering correlation on straight roads is not as strong as observed on curvy roads. However, eye-steering correlation measured through correlation coefficient and time delay between two movements is sensitive to different types of distraction. Time delay mediates changes in lane position and the eye-steering system predicts breakdowns in lane keeping. This dissertation contributes to developing a distraction detection system that integrates visual and steering behavior. More broadly, these results suggest that integrating eye and steering data can be helpful in detecting and mitigating impairments beyond distraction, such as those associated with alcohol, fatigue, and aging.
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Al, Mahdawi Basil Mohamed Nouri. "Senior monitoring by using sensors network and optical metrology". Thesis, Bourgogne Franche-Comté, 2017. http://www.theses.fr/2017UBFCD085.
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L’objectif du travail de cette thèse est la contribution au développement de nouvelles techniques dans le domaine dessystèmes de détection sans marqueur pour une utilisation dans trois domaines vitaux de la santé en utilisant des capteursinnovants et peu coûteux. Pour la réalisation de nos objectifs nous avons eu recours principalement à de l’électroniqueembarquées et du traitement du signal en utilisant le capteur Kinect. Des résultats encourageants ont été obtenus et sontprésentés tout au long de cette thèse. Dans la première partie de ce travail, nous présentons un nouveau système desurveillance visuelle sans marqueur en temps réel pour détecter et suivre les personnes âgées et surveiller leurs activitésdans leur environnement intérieur en utilisant un réseau de capteurs Kinect. Le système identifie également l’événementde chute des personnes âgées sous surveillance. Dans la deuxième partie nous utilisons également le capteur Kinectmais cette fois ci pour la détection sans marqueur des mouvements de la tête d’un patient lors d’un examen utilisant LaTomographie par Emission de Positons (CT/PET) du cerveau. Ce travail est basé sur la compensation de la dégradationde l’image TEP due aux mouvements de la tête du patient. Pour nos essais un cobaye dit « fantôme » a été réalisé,les résultats sur le fantôme sont prometteur ce qui a donné lieu à un test sur un vrai patient volontaire. Les résultatsfinaux montrent l’efficacité de ce nouveau système. La troisième partie du travail présente la mise en oeuvre d’un nouveausystème intelligent pour contrôler un fauteuil roulant électrique par des mouvements spéciaux de la tête toujours sansmarqueur. Un algorithme adapté est conçu pour détecter en continu les degrés des mouvements du visage en utilisant lecapteur Kinect. Fautes de fauteuil roulant électrique, le système a été testé sur un véhicule radio commandéThe objective of the work of this thesis is the contribution in developing novel technical methods in the field of marker-lesssensing systems for use in three vital health areas by using new inexpensive sensors. Several scientific areas are involvedin achieving our objective such as; electronics and signal processing by using the Kinect sensor. Encouraging results wereachieved as presented throughout this thesis. In the first part of this work we present a new real-time marker-less visualsurveillance system for detecting and tracking seniors and monitoring their activities in the indoor environment by usingnetwork of Kinect sensors. The system also identifies the fall event with the elderly. In the second part, we present anew approach for a marker-less movement detection system for influential head movements in the brain Positron EmissionTomography imaging (CT/PET) by employing the Kinect sensor. This work addresses the compensation of the PET imagedegradation due to subject’s head movements. A developed particular phantom and volunteer studies were carried out.The experimental results show the effectiveness of this new system. The third part of the work presents the design andimplementation of a new smart system for controlling an electric wheelchair by special mark-less head movements. Anadaptable algorithm is designed to continuously detect the rotation degrees of the face pose using the Kinect sensor inreal-time that are interpreted as controlling signals through a hardware interface for the electric wheelchair actuators
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Giesel, M., A. Yakovleva, Marina Bloj, A. R. Wade, A. M. Norcia y J. M. Harris. "Relative contributions to vergence eye movements of two binocular cues for motion-in-depth". Springer Nature Group, 2019. http://hdl.handle.net/10454/17514.
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YesWhen we track an object moving in depth, our eyes rotate in opposite directions. This type of “disjunctive” eye movement is called horizontal vergence. The sensory control signals for vergence arise from multiple visual cues, two of which, changing binocular disparity (CD) and inter-ocular velocity differences (IOVD), are specifically binocular. While it is well known that the CD cue triggers horizontal vergence eye movements, the role of the IOVD cue has only recently been explored. To better understand the relative contribution of CD and IOVD cues in driving horizontal vergence, we recorded vergence eye movements from ten observers in response to four types of stimuli that isolated or combined the two cues to motion-in-depth, using stimulus conditions and CD/IOVD stimuli typical of behavioural motion-in-depth experiments. An analysis of the slopes of the vergence traces and the consistency of the directions of vergence and stimulus movements showed that under our conditions IOVD cues provided very little input to vergence mechanisms. The eye movements that did occur coinciding with the presentation of IOVD stimuli were likely not a response to stimulus motion, but a phoria initiated by the absence of a disparity signal.
Supported by NIH EY018875 (AMN), BBSRC grants BB/M001660/1 (JH), BB/M002543/1 (AW), and BB/MM001210/1 (MB).
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Mills, Clayton Harry. "Movement and Force Measurement Systems as a Foundation for Biomimetic Research on Insects". Thesis, University of Canterbury. Electrical and Computer Engineering, 2008. http://hdl.handle.net/10092/2895.
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During the undertaken research and development, two major systems were designed. These were; a prototype force sensor, and a movement measurement system. Both the developed systems were designed for the intended field of insect research, but were developed using very different underlying principles. The force measurement system uses the piezo-electric effect induced in piezo-electric bimorph elements to produce a measure of force exerted on the sensor. The movement measurement system on the other hand uses computer vision (CV) techniques to find and track the three dimensional (3D) position of markers on the insect, and thereby record the pose of the insect.
To further increase the usefulness of the two measurement systems, a prototype graphical user interface (GUI) was produced to encapsulate the functionality of the systems and provide an end user with a more complete and functional research tool. The GUI allows a user to easily define the parameters required for the CV operations and presents the results of these operations to the user in an easily understood visual format. The GUI is also intended to display force measurements in a graphical means to make them easily interpreted. The GUI has been named Weta Evaluation Tracking and Analysis (WETA).
Testing on the developed prototype force sensor shows that the piezo-electric bimorph elements provide an adequate measure of force exerted on them, when the voltage signal produced by an element is integrated. Furthermore, the testing showed that the developed force sensor layout produces an adequate measure of forces in the two horizontal linear degrees of freedom (DOF), but the prototype did not produce a good measure of forces
in the vertical linear DOF.
Development and testing of the movement measurement system showed that stereo vision techniques have the ability to produce accurate measurements of 3D position using two cameras. Although, when testing these techniques with one of the cameras replaced by a mirror, the system produced less than satisfactory results. Further testing on the feature detection and tracking portions of the movement system showed that even though these systems were implemented in a relatively simple way, they were still adequate in their associated operations. However, it was found that with some simple changes in colour spaces used during feature detection, the performance of the feature detection system in varying illumination was greatly improved. The tracking system on the other hand, operated adequately using just its associated basic principles.
During the development of both prototype measurement systems, a number of conclusions were formulated that indicated areas of future development. These areas include; advanced force sensor configurations, force sensor miniaturisation, design of a force plate, improvement of feature detection and tracking, and refining of the stereo vision equipment.
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Jenkins, Jeffrey Lyne. "Alleviating Insider Threats: Mitigation Strategies and Detection Techniques". Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/297023.
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Insider threats--trusted members of an organization who compromise security--are considered the greatest security threat to organizations. Because of ignorance, negligence, or malicious intent, insider threats may cause security breaches resulting in substantial damages to organizations and even society. This research helps alleviate the insider threat through developing mitigation strategies and detection techniques in three studies. Study 1 examines how security controls--specifically depth-of-authentication and training recency--alleviate non-malicious insider threats through encouraging secure behavior (i.e., compliance with an organization's security policy). I found that `simpler is better' when implementing security controls, the effects of training diminish rapidly, and intentions are poor predictors of actual secure behavior. Extending Study 1's finding on training recency, Study 2 explains how different types of training alleviate non-malicious insider threat activities. I found that just-in-time reminders are more effective than traditional training programs in improving secure behavior, and again that intentions are not an adequate predictor of actual secure behavior. Both Study 1 and Study 2 introduce effective mitigation strategies for alleviating the non-malicious insider threat; however, they have limited utility when an insider threat has malicious intention, or deliberate intentions to damage the organization. To address this limitation, Study 3 conducts research to develop a tool for detecting malicious insider threats. The tool monitors mouse movements during an insider threat screening survey to detect when respondents are being deceptive. I found that mouse movements are diagnostic of deception. Future research directions are discussed to integrate and extend the findings presented in this dissertation to develop a behavioral information security framework for alleviating both the non-malicious and malicious insider threats in organizations.
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Sullivan, John B. "The application of an artificial neural network to a turning movement detector system". Ohio : Ohio University, 1991. http://www.ohiolink.edu/etd/view.cgi?ohiou1183987292.
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Etudo, Ugochukwu O. "Automatically Detecting the Resonance of Terrorist Movement Frames on the Web". VCU Scholars Compass, 2017. http://scholarscompass.vcu.edu/etd/4926.
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The ever-increasing use of the internet by terrorist groups as a platform for the dissemination of radical, violent ideologies is well documented. The internet has, in this way, become a breeding ground for potential lone-wolf terrorists; that is, individuals who commit acts of terror inspired by the ideological rhetoric emitted by terrorist organizations. These individuals are characterized by their lack of formal affiliation with terror organizations, making them difficult to intercept with traditional intelligence techniques. The radicalization of individuals on the internet poses a considerable threat to law enforcement and national security officials. This new medium of radicalization, however, also presents new opportunities for the interdiction of lone wolf terrorism. This dissertation is an account of the development and evaluation of an information technology (IT) framework for detecting potentially radicalized individuals on social media sites and Web fora. Unifying Collective Action Framing Theory (CAFT) and a radicalization model of lone wolf terrorism, this dissertation analyzes a corpus of propaganda documents produced by several, radically different, terror organizations. This analysis provides the building blocks to define a knowledge model of terrorist ideological framing that is implemented as a Semantic Web Ontology. Using several techniques for ontology guided information extraction, the resultant ontology can be accurately processed from textual data sources. This dissertation subsequently defines several techniques that leverage the populated ontological representation for automatically identifying individuals who are potentially radicalized to one or more terrorist ideologies based on their postings on social media and other Web fora. The dissertation also discusses how the ontology can be queried using intuitive structured query languages to infer triggering events in the news. The prototype system is evaluated in the context of classification and is shown to provide state of the art results. The main outputs of this research are (1) an ontological model of terrorist ideologies (2) an information extraction framework capable of identifying and extracting terrorist ideologies from text, (3) a classification methodology for classifying Web content as resonating the ideology of one or more terrorist groups and (4) a methodology for rapidly identifying news content of relevance to one or more terrorist groups.
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Twyman, Nathan W. "Automated Human Screening for Detecting Concealed Knowledge". Diss., The University of Arizona, 2012. http://hdl.handle.net/10150/222874.
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Screening individuals for concealed knowledge has traditionally been the purview of professional interrogators investigating a crime. But the ability to detect when a person is hiding important information would be of high value to many other fields and functions. This dissertation proposes design principles for and reports on an implementation and empirical evaluation of a non-invasive, automated system for human screening. The screening system design (termed an automated screening kiosk or ASK) is patterned after a standard interviewing method called the Concealed Information Test (CIT), which is built on theories explaining psychophysiological and behavioral effects of human orienting and defensive responses. As part of testing the ASK proof of concept, I propose and empirically examine alternative indicators of concealed knowledge in a CIT. Specifically, I propose kinesic rigidity as a viable cue, propose and instantiate an automated method for capturing rigidity, and test its viability using a traditional CIT experiment. I also examine oculomotor behavior using a mock security screening experiment using an ASK system design. Participants in this second experiment packed a fake improvised explosive device (IED) in a bag and were screened by an ASK system. Results indicate that the ASK design, if implemented within a highly controlled framework such as the CIT, has potential to overcome barriers to more widespread application of concealed knowledge testing in government and business settings.
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Ulbrich, Jakub. "Zabezpečovací systém s komunikací přes mobilní telefon". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-218016.
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This thesis deals with the question of electronic security systems. In the forepart are described electronic security system components such as keyboards, detectors, alarm devices etc. Various methods of security or de-security of properties, trespassing and other events detection methods, and ways of alarm calling are described there too. The next part of the master’s thesis focuses on the construction of an alarm system which is designed for security of a common-size flat with one entry. The system manages to control up to four movement detectors. The operation of the system is handled by a 16 button keyboard, and easy orientation is provided thanks to a liquid crystal display. The alarm is signaled by an indoor alert siren, however, other alarm announcing devices with an input matched for the log. 0 or log. 1 reception can be connected too. The system contains communication equipment (mobile phone) which signals alarm at a distance to the three telephone numbers. User can use a distance control by text message to unlock system or to determine its status. The system is controlled by the microcontroller AVR ATmega16, the product of Atmel company. A brief description of all components of the electronic alarm system is included in this work.
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Liu, Yung-Chun y 劉勇均. "EEG Signal Analysis System for Finger Movement Detection". Thesis, 2004. http://ndltd.ncl.edu.tw/handle/23412415412673544100.
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碩士國立成功大學
資訊工程學系碩博士班
92
Many neurological diseases, such as stroke and spinal cord injury, disrupt the connections between brain cortex and muscles. Besides, some other diseases may destruct the muscle and make it functionless. All these diseases interfere with the voluntary movements of the subjects and influence their ability to accomplish the attempted task. Brain-computer interface (BCI), which defines an artificial alternative output from the brain cortex to make communication with their surrounding targets, can improve above deficits. The most common way of BCI is to give control signals based on the analysis of Electroencephalogram (EEG) signals. And the recognition of finger movements has been one of the most important issues in this field. In the previous researches, the length of EEG trials for analysis were usually between 4 to 10 seconds, therefore it would have difficulties in real-time applications. For this reason, we study the technique of analyzing the EEG signals which have the length of one second, and construct a real-time EEG recognition system based on it for detecting finger movements. We adopt the strategy, named Active Time Segment Selection, to pick the most appropriate time segment of the EEG trial for the recognition of finger movements. And the classifier is trained with the information of this segment in all trials. The integrated processes with the above-mentioned functions form a two-staged recognition system to classify the finger motions in real-time. Besides, we propose an automatic approach to provide statistical analysis on the results of recognition in each stage. From the results of the experiment, it has shown that our system can distinguish a finger movement or a non-movement from the input EEG signal sequences, and further recognize the movement as a left or a right one successfully. We expect to use the system in controlling clinical assistive devices in the future, and benefit the subjects with neurological diseases or limb disabilities.
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Tsai, Sung-Hua y 蔡松樺. "A System of Movement Detection and Evaluation with FMS". Thesis, 2016. http://ndltd.ncl.edu.tw/handle/aq4h6g.
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碩士國立雲林科技大學
電子工程系
104
The main intention of this study is to improve the evaluation approach of measurement devices of Functional Movement Screen. Previous measurement results of FMS were only judged by subjective assessment of coach or trainer and were lack of digitized data so that the users were unable to comprehend their conditions immediately. Therefore, this study applies image technology to FMS and establishes a system of movement detection and evaluation which provides scientific data reports to users. The system captures images by two web cameras and ties nine orange mark points in users’ bodies. In the following steps, the system analyzes these orange markers which cameras capture from users’ bodies through image processing technology and records the postures information during users perform evaluation actions. Moreover, real-time image processing calculates the angles of each body part when users perform actions. Finally, the system automatically generates excel evaluation report that enables users to understand the current conditions of their bodies immediately. Eight participants with different heights, test twice a week and for two weeks continuously. The testing results of image accuracy indicates that orange markers captured accuracy rate of seven evaluated actions reaches over 80 percent which implies the system has high accuracy at capturing different height participants' postures. Furthermore, the retest reliabilities of system show moderately correlated(R>0.5) and highly correlated(R>0.7) in measuring angles of postures at different time which means the system is stable. In conclusion, the measurement result of FMS of the system possesses great valuable reference.
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Lavergne, Anne. "Computer vision system for head movement detection and tracking". Thesis, 1999. http://hdl.handle.net/2429/9683.
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The increased popularity of applications requiring head tracking, such as teleconferencing and
virtual reality, have fuelled research efforts to provide computer vision solutions to the problem
of real-time head movement tracking. The attractiveness of this type of solution rests on the fact
that head tracking can be performed without the use of expensive and cumbersome physical
devices.
We propose a computer vision approach that detects the head movements of a user seated at a
computer workstation. We model head translation and head rotation using distinct sets of
templates synthesized from an initially captured image of the head and representing this head in
various positions (and sizes) and orientations. Using correlation-based template matching, we
achieve detection by correlating these sets of templates against each image of the head captured
by a camera positioned on the top of the monitor. The best-correlating template from the set
modelling head translation and the best from the set modelling head rotation represent good
approximations of the three-dimensional position and orientation of the head in the scene,
respectively. We improve on these approximations by defining two functions that interpolate the
correlation scores of each set and by obtaining the minimum of each of these functions. We use
these two minima, which represent head position and orientation, to synthesize a new template
based on the initially captured image of the head. This new synthesized template represents the
image of the head that most closely approximates the head position and orientation in the scene.
Head movement tracking is performed by comparing the closest approximation of the head found
in two consecutive images of the scene.
We have implemented our head movement tracking approach and found our system to track head
position, on average, to within one pixel of the measured head position in both the x- and y-axis
directions, and to detect head size (width and height), on average, to within one and two pixels of
the measured head width and height, respectively. Our head movement tracking system tracks
head rotations, on average, to within 1.4° of the measured angles.. Our tracker is capable of
processing up to eight captured images per second.
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Berners, Ann C. "An ultrasonic time-of-flight system for hand movement detection". 1986. http://catalog.hathitrust.org/api/volumes/oclc/14927159.html.
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Thesis (M.S.)--University of Wisconsin-Madison, 1986.Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaf 12).
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Wang, Cheng-Yuan y 王正元. "Development of a fetal movement detection system with adaptive filter". Thesis, 2019. http://ndltd.ncl.edu.tw/handle/7gmy33.
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碩士南臺科技大學
電機工程系
107
In the declining birth rate ones, any abnormalities that occur during pregnancy are easy to worry about parents. How to continuously monitor the status of the fetus during pregnancy is the current clinical care direction for high-risk pregnant women. Fetal movement signals are one of the simplest criteria for assessing fetal activity in clinical practice. However, the fetal movement measuring instruments used in hospitals are susceptible to self-subjective influences, which often results in uncountable counting results and cannot be measured for a long time. This study will improve previous research designs, improve with new multi-channel filters, multiple data storage and transmission methods, and improve the design with clinical advice. In this study, we used a Kalman filter to filter out the inciting offset signal of pregnant woman and judge the place, duration and relative force of fetal movements with the multi-channel IMU sensing algorithm. The system can transmit fetal movement data to the remote interface through Bluetooth 4.0. It can also read the fetal movement data to the interface through wired transmission and the storage function of secure digital card to avoid pregnant women’s concerns of radiation exposure of wireless transmission. The device is designed to be more adaptable for the belly surface of pregnant women. It is made of thermoplastic elastomer and medical grade silicone to reduce the skin allergic reaction and improve wearing comfort. The simulation test results indicated that the accuracy of 12 fetal movement positions was 80.83%, and the error rate of duration between 5 seconds to 15 seconds were less than 1.6%. The experiment of the relative force of 5 mm to 9 mm displacement indicated that the error rate was less than 6% through the relative force coefficient compensation formula. The error rate was less than 0.2% when the uterine contraction lasted between 30 seconds to 50 seconds, and the error rate of the relative force of 7 mm to 9 mm displacement was less than 1.6%. It is expected that through the device proposed in this study, the defects of clinical counting fetal movement will be improved, and the fetal movement status of pregnant women will be grasped in a more objective manner, and it will be used for future clinical fetal movement monitoring.
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Wang, Kai-Wei y 王凱偉. "Upper-Limb-movement Classification System ofPalsy Children Based on Arm Motion Detection". Thesis, 2005. http://ndltd.ncl.edu.tw/handle/64299782980169243871.
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碩士長庚大學
電機工程研究所
93
Cerebral Palsy is mean damage to the brain, causing non-progressive brain injury, such as limbs palsy, epilepsy, involuntary movements, poor coordination. In the past, the study for cerebral palsy children with physical impairments are usually focused on their lower limbs impairments, but not upper limbs. Moreover, the evaluation of movements is mainly decided by clinic physician with their experience. However, this manner can’t provide a spec enough. The paper proposes an upper limbs movements evaluation system, in view Cerebral Palsy child hand movement smoothness evaluation. This system consists of three stages, i.e. image acquisition stage, segmentation stage and data classification stage. In the stages of image acquisition and segmentation, bilinear interpolation, color space transformation and image morphology, are used for hand tracking, respectively. Then, momentum analysis parameter to operation in coordination upper-limbs evaluate equation, to conduct data classification. From the experimental result, it is proved that this proposed system show, compare with Normalized Cross Correlation and Otsu, can be obtain high rate of accuracy; data judge divided into two kinds of A and B, A represents slightly, B represents seriously.
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Wun, Da-Cian y 温達乾. "Ipsilateral Dual SIL-Radar System for Vital Sign Detection with Random Body Movement Cancellation". Thesis, 2015. http://ndltd.ncl.edu.tw/handle/44533297795176692810.
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碩士國立中山大學
電機工程學系研究所
104
This thesis studies a vital-sign detection system based on a dual self-injection-locked (SIL) radar to resolve the interference due to random body motion, which is one of the challenging issues in this field. The system creates the 180 degrees phase difference between the two different paths in the dual SIL radar to achieve the random body motion cancellation condition in detecting vital signs such as respiration and heart rates. The system architecture and experimental setup are constructed through a step-by-step procedure. Firstly, a random object motion is generated by shaking a metal plate. Secondly, the phase shifter is tuned to cancel the Doppler shift caused by the motion of the object under a well-balanced system architecture. Finally, the dual SIL radar is used to detect vital signs under random body motion with comparison to the signal SIL radar. Only the dual SIL radar can successfully detect the normal and high respiration and heart rates of a human before and after exercise, respectively, with random body motion.
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Chen, Pai-Hung y 陳百宏. "Fabrication and analysis for the actuation movement of automobile-used relay via automatic detection system". Thesis, 2006. http://ndltd.ncl.edu.tw/handle/05437170626446237861.
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碩士國立彰化師範大學
機電工程學系
94
This thesis mainly focuses on developing an automatic inspection system for automotive relays. The LabVIEW platform is used to provide a control integration intenface. The conventional apparatus and human power has been replaced. The apparatus used in traditional way of inspecting the relays contains oscilloscope, LCR tester, and power supply. Thus, the relay inspection platform for automotives constructed in this thesis using the programming language to combine the function of oscilloscope with an easy-setup circuit modulus which is used to replace the power supply in the LabVIEW software. The LCR tester detector with function of measuring the low-resistance, is linked via the internal GBIB of LCR tester and PC interface for inspection. The detected values can be effectively calculated and analyzed. The data sheet can be generated and pop-up automatically for the data establishment and integration. About the switch motion of relays, this thesis uses a 2D finite element analysis software called FEMM(Finite Element Method Magnetics) to calculate the variation of flux distribution and the switch force in the axisymmetric model, which provide a innovation way for the designer of relays and could saves plenty of time in developing.
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Jiang, Wei-Ling y 江偉凌. "Design of eye movement detection system based on electrooculography signals and their human-computer interaction applications". Thesis, 2012. http://ndltd.ncl.edu.tw/handle/35340531493212140290.
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碩士國立交通大學
影像與生醫光電研究所
100
In assistive research area, human-computer interface (HCI) technology is used to help disable people by conveying their intention and thinking to the outside world. Many HCI systems based on eye movement have been proposed to assistive disable people. However, due to the complexity of algorithm and difficulty of hardware implementation, there are rare general purpose designs considering the practicality and stability in real-life. Therefore, to solve these limitations and problems, a HCI system based on electrooculography (EOG) is proposed in this study. The proposed classification algorithm provides the eye state detection including fixation, saccade and blink. Moreover, in saccade detection, this algorithm can distinguish ten kind of saccade movements (i.e., up, down, left, right, much left, much right, up-left, down-left, up-right and down-right). In addition, we development a HCI system based on eye movement classification algorithm. This system provides an eye-dialing interface that can be facilitated to improve the life of disable people. The significant results are achieved that proved the performance of the proposed classification algorithm. Moreover, the EOG-based system, which can detect ten different eye movement features, is potential to be performed in real-life applications.
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Goshev, Stefan Antoanov. "Analysis of smuggler movement on multiple transportation networks". Thesis, 2011. http://hdl.handle.net/2152/ETD-UT-2011-05-3357.
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We analyze an interdiction problem in which a nuclear-material smuggler can traverse multiple transportation networks, wherein each edge has an indigenous probability of evasion. Our objective is to determine the optimal locations of a limited number of radiation detectors at United States ports of entry across multiple networks (maritime, road and rail) so as to minimize the smuggler's total probability of evasion, from origin to destination. We choose geographically diverse potential origins and give the smuggler freedom to move across and between transportation networks. Further, we consider two different models of smuggler behavior in this context. Our analysis aims to provide a complete prioritization and picture of the threat at all ports of entry, leading to insight into good practical locations for detectors.text
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Vefaghnematollahi, Shayesteh. "Babykick: development of a wearable system for detecting fetal movements during pregnancy". Thesis, 2020. http://hdl.handle.net/1828/12517.
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Decreased fetal movement can indicate uncommon complication of labor; in response,
we have developed a non-invasive, wearable monitoring tool to objectively
assess fetal movement called the Babykick device. The novelty of this device is that
it moves away from a traditional subjective assessment of fetal movement to an objective,
quantitative measurement that remains low-cost. The designed tool refrains
from utilizing expensive and less available monitoring modalities such as ultrasound
imaging, Doppler velocimetry or cardiotocography. Instead, the wearable consists of
a piezo-sensitive belt that is wirelessly connected to a phone or tablet. It can be used
to record the frequency and amplitude of fetal movements perceived passively and
non-invasively on the surface of the abdomen of the pregnant woman for a period of
up to one hour while she is supine or seated in a reclined position. The ndings from
the Babykick device will be correlated with those from subjective maternal assessment
and the observation of the Research Coordinator during the test. This low-cost,
non-invasive wearable belt could potentially reduce negative outcomes such as stillbirth,
perinatal mortality and neonatal morbidity in low- to middle-income settings
and is anticipated to be useful for long-term home monitoring.Graduate
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Huanh, Ying-Wei y 黃映維. "The Analysis and Application of a Lie Detection System using Facial Micro-Movements". Thesis, 2017. http://ndltd.ncl.edu.tw/handle/dtc4d8.
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碩士國立清華大學
計量財務金融系
105
Facial micro-expressions are brief, involuntary expressions appeared on the face of people who are trying to conceal or repress emotions. This paper developed a questionnaire containing control questions and relevant questions. We analyze the motions of key features on the faces and the appearance of the micro-expressions, we quantify the characteristic of telling lies by observing a sequence of frames extracted from videos. In the model, we test several factors which including eyes’ and mouth’s micro movements, and then fit the logistic regression model to find the main effect on the facial movements when telling lies. The empirical results indicate that people tend to lie while decreasing the horizontal length of their mouths. Furthermore, the vertical width of eyes tends to change significantly in a very short period while lying. The classification result of model shows that sensitivity = 74.36% as the proportion of deceptive response being classified correctly; and the overall classification accuracy is 62.23%. We also find out that when people are answering high-stakes questions, our model will achieve a 71.79% classification accuracy in deception response with an overall accuracy as 65.38%, which is higher than the accuracy of all data.
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Chen, Xuan-Hong y 陳炫宏. "Analysis and Development of the Eye Movement Tracking System without Detecting Light Source". Thesis, 2012. http://ndltd.ncl.edu.tw/handle/29479674115840451325.
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碩士國立臺灣海洋大學
通訊與導航工程學系
100
With the rapid changes in technology, a simple button functions have gradually unable to meet the needs and convenience of modern people. The most important thing is that can be communicated with other people. However, there are some minority groups like Amyotrophic Lateral Sclerosis (A.L.S) or Motor Neuron Disease (M.N.D) patients; they can’t communicate with others by using computer as normal persons. Adopting only two low-cost cameras, an eye-tracking system will be investigated such that the disabled people can use eyes to operate computer instead of hands without detection light source. The first camera uses the Pan-focus function to capture the image around the eye which will be converted into binary using the critical threshold. To reduce noise interference, the deconstruction of the elements of erosion and expansion will be employed. And then the dimensional coordinate transformation line with linear grid mapping method will be used to calculate the eye gaze position such that the eye center position can be identified. The second camera will be applied to compensate head movement error. Two characteristic points will be identified by HSV and then the center and angle between these two points will be used to compensate the estimation of the head motion. Disabled persons through the eye tracking system can browse the Internet, watch video, play games, operate home appliances, type, and pronounce.
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Hawley, Megan Lynn. "Interdicting smuggler movement with transparent and non-transparent assets". Thesis, 2012. http://hdl.handle.net/2152/ETD-UT-2012-05-5765.
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We analyze an interdiction problem in which a nuclear-material smuggler can traverse the rail and road ports of entry (POEs) along the Mexican and Canadian borders of the United States. Our objective is to determine the optimal locations of a limited number of transparent and non-transparent assets so as to minimize the smuggler’s total probability of evasion, from origin to destination. We choose origins in Mexico and Canada and give the smuggler a diverse set of destinations to choose from. Our analysis aims to provide a complete prioritization and picture of the threat at Mexican and Canadian POEs, leading to insight into practical locations for transparent and non-transparent assets.text
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Pereira, Ricardo Daniel Cardoso. "AIS Data Visualization applied to the identification of anomalous vessels' movements on the Portuguese maritime territory". Master's thesis, 2018. http://hdl.handle.net/10316/83542.
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Dissertação de Mestrado em Engenharia Informática apresentada à Faculdade de Ciências e TecnologiaHá poucos anos atrás o Sistema de Identificação Automática (AIS) foi definido como o standard internacional para a comunicação entre navios com o objetivo de melhorar a segurança marítima, mas hoje em dia é utilizado para muitos mais fins porque os seus dados têm o potencial de conseguirem mapear todo o tráfego marítimo de uma determinada zona. Um desses fins é ajudar as autoridades a detetarem comportamentos anómalos através da análise dos movimentos dos navios. Desta forma, vários trabalhos científicos relacionados com dados do AIS têm sido publicados, apresentando abordagens de aprendizagem computacional e de visualização de informação, em áreas tão distintas como a extração de trajetórias, visualização de tráfego e deteção de anomalias. No entanto, considerando esta última área, apenas abordagens de aprendizagem computacional foram propostas, enquanto os trabalhos na área da visualização de informação tendem a propor representações do tráfego dos navios sem qualquer destaque aos comportamentos anómalos. Assim sendo, a presente tese tem como objetivo o desenvolvimento de estratégias de visualização capazes de identificar comportamentos anómalos, com a assistência de técnicas de análise de dados, e o teste dessas estratégias com dados AIS da zona marítima Portuguesa. Estas estratégias foram implementadas numa plataforma e incluem abordagens para uma análise geral dos dados e para a deteção de tipos específicos de comportamentos anómalos. A validação, feita através de casos de estudo, mostrou que as abordagens funcionam e que podem ser utilizadas como ferramenta de suporte aos peritos da área.
A few years ago the Automatic Identification System (AIS) was introduced as the international communication standard for vessels with the propose of improving maritime safety, but nowadays it is used for more proposes mainly because its data has the potential of mapping with detail the entire maritime traffic of an area. One of this new proposes is assisting law enforcement in detecting abnormal behaviors through movement analysis of the vessels. Because of that, several scientific works addressing AIS data have been published based on machine learning and data visualization approaches, in distinct areas such as trajectory mining, traffic visualization and anomaly detection. However, considering this last area, only machine learning approaches have been proposed, while the data visualization works tend to be focused on representing the vessel's traffic without any consideration for the anomalous behaviors. Therefore, this thesis is focused in developing visualization strategies that are able to identify these behaviors, with the assistance of data analysis, and in testing them with AIS data from the Portuguese maritime zone. These strategies were implemented on a platform and they include approaches for a general analysis of the data and for detecting specific types of anomalous behaviors. The validation, made through case studies, showed that the approaches are effective and can be used as a support tool for the domain experts.