Academic literature on the topic 'Field's Visual Information Transformation Test'
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Journal articles on the topic "Field's Visual Information Transformation Test"
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Sarrouti, Mourad, Asma Ben Abacha, and Dina Demner-Fushman. "Goal-Driven Visual Question Generation from Radiology Images." Information 12, no. 8 (2021): 334. http://dx.doi.org/10.3390/info12080334.
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Visual Question Generation (VQG) from images is a rising research topic in both fields of natural language processing and computer vision. Although there are some recent efforts towards generating questions from images in the open domain, the VQG task in the medical domain has not been well-studied so far due to the lack of labeled data. In this paper, we introduce a goal-driven VQG approach for radiology images called VQGRaD that generates questions targeting specific image aspects such as modality and abnormality. In particular, we study generating natural language questions based on the visual content of the image and on additional information such as the image caption and the question category. VQGRaD encodes the dense vectors of different inputs into two latent spaces, which allows generating, for a specific question category, relevant questions about the images, with or without their captions. We also explore the impact of domain knowledge incorporation (e.g., medical entities and semantic types) and data augmentation techniques on visual question generation in the medical domain. Experiments performed on the VQA-RAD dataset of clinical visual questions showed that VQGRaD achieves 61.86% BLEU score and outperforms strong baselines. We also performed a blinded human evaluation of the grammaticality, fluency, and relevance of the generated questions. The human evaluation demonstrated the better quality of VQGRaD outputs and showed that incorporating medical entities improves the quality of the generated questions. Using the test data and evaluation process of the ImageCLEF 2020 VQA-Med challenge, we found that relying on the proposed data augmentation technique to generate new training samples by applying different kinds of transformations, can mitigate the lack of data, avoid overfitting, and bring a substantial improvement in medical VQG.
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Valiente García, David, Lorenzo Fernández Rojo, Arturo Gil Aparicio, Luis Payá Castelló, and Oscar Reinoso García. "Visual Odometry through Appearance- and Feature-Based Method with Omnidirectional Images." Journal of Robotics 2012 (2012): 1–13. http://dx.doi.org/10.1155/2012/797063.
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In the field of mobile autonomous robots, visual odometry entails the retrieval of a motion transformation between two consecutive poses of the robot by means of a camera sensor solely. A visual odometry provides an essential information for trajectory estimation in problems such as Localization and SLAM (Simultaneous Localization and Mapping). In this work we present a motion estimation based on a single omnidirectional camera. We exploited the maximized horizontal field of view provided by this camera, which allows us to encode large scene information into the same image. The estimation of the motion transformation between two poses is incrementally computed, since only the processing of two consecutive omnidirectional images is required. Particularly, we exploited the versatility of the information gathered by omnidirectional images to perform both an appearance-based and a feature-based method to obtain visual odometry results. We carried out a set of experiments in real indoor environments to test the validity and suitability of both methods. The data used in the experiments consists of a large sets of omnidirectional images captured along the robot's trajectory in three different real scenarios. Experimental results demonstrate the accuracy of the estimations and the capability of both methods to work in real-time.
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Dowell, Catherine, Alen Hajnal, Wim Pouw, and Jeffrey B. Wagman. "Visual and Haptic Perception of Affordances of Feelies." Perception 49, no. 9 (2020): 905–25. http://dx.doi.org/10.1177/0301006620946532.
Full textAbstract:
Most objects have well-defined affordances. Investigating perception of affordances of objects that were not created for a specific purpose would provide insight into how affordances are perceived. In addition, comparison of perception of affordances for such objects across different exploratory modalities (visual vs. haptic) would offer a strong test of the lawfulness of information about affordances (i.e., the invariance of such information over transformation). Along these lines, “feelies”— objects created by Gibson with no obvious function and unlike any common object—could shed light on the processes underlying affordance perception. This study showed that when observers reported potential uses for feelies, modality significantly influenced what kind of affordances were perceived. Specifically, visual exploration resulted in more noun labels (e.g., “toy”) than haptic exploration which resulted in more verb labels (i.e., “throw”). These results suggested that overlapping, but distinct classes of action possibilities are perceivable using vision and haptics. Semantic network analyses revealed that visual exploration resulted in object-oriented responses focused on object identification, whereas haptic exploration resulted in action-oriented responses. Cluster analyses confirmed these results. Affordance labels produced in the visual condition were more consistent, used fewer descriptors, were less diverse, but more novel than in the haptic condition.
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Liu, Xiaolin, and Robert A. Scheidt. "Contributions of Online Visual Feedback to the Learning and Generalization of Novel Finger Coordination Patterns." Journal of Neurophysiology 99, no. 5 (2008): 2546–57. http://dx.doi.org/10.1152/jn.01044.2007.
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We explored how people learn new ways to move objects through space using neuromuscular control signals having more degrees of freedom than needed to unambiguously specify object location. Subjects wore an instrumented glove that recorded finger motions. A linear transformation matrix projected joint angle signals (a high-dimensional control vector) onto a two-dimensional cursor position on a video monitor. We assessed how visual information influences learning and generalization of novel finger coordination patterns as subjects practiced using hand gestures to manipulate cursor location. Three groups of test subjects practiced moving a visible cursor between different sets of screen targets. The hand-to-screen transformation was designed such that the different sets of targets (which we called implicit spatial cues) varied in how informative they were about the gestures to be learned. A separate control group practiced gesturing with explicit cues (pictures of desired gestures) without ongoing cursor feedback. Another control group received implicit spatial cueing and feedback only of final cursor position. We found that test subjects and subjects provided with explicit cues could learn to produce desired gestures, although training efficacy decreased as the amount of task-relevant feedback decreased. Although both control groups learned to associate screen targets with specific gestures, only subjects provided with online feedback of cursor motion learned to generalize in a manner consistent with the internal representation of an inverse hand-to-screen mapping. These findings suggest that spatial learning and generalization require dynamic feedback of object motion in response to control signal changes; static information regarding geometric relationships between controller and endpoint configurations does not suffice.
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Muhammad, Safdar, Ming Ronnier Luo, and Xiao Yu Liu. "Improvement of JPEG for Color Images by Incorporation of CAM02-UCS and Cubic Spline Interpolation." Applied Mechanics and Materials 731 (January 2015): 7–12. http://dx.doi.org/10.4028/www.scientific.net/amm.731.7.
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Image data is always a major fraction of the huge data to be stored or transmitted. That is why researchers have been evolved in finding out different ways and techniques to increase compression rate and reduce information loss. This research investigated the improvement of JPEG compression algorithm by incorporating cubic spline interpolation (CSI) in the sampling stage and four different color spaces in the color space transformation stage. JPEG 1992 standard was considered and results were compared with previous works done by different researchers. The sampling and color space transformation stages of the JPEG algorithm were taken into consideration. In the color space transformation stage, two linear and non-uniform color spaces RGB and YIQ, and two uniform color spaces CIELAB and the CIECAM02 based uniform color space CAM02-UCS were incorporated and investigated. The sampling stage of JPEG contributes much to improve the compression rate at the cost of loss of some information. Current study incorporated cubic spline interpolation technique to reduce the information loss at this typical stage. The CIEDE2000 color difference formula, which is best correlated with the human visual perception, was used as metric to investigate performance of newly proposed improvements in JPEG algorithm for color image compression. The test results showed that the proposed modifications in the two stages of JPEG algorithm improved its performance in terms of compressibility and quality, and the difference in performance was statistically significant. Psychophysical experiments were also performed which validated the test results.
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NIITSUMA, HIROTAKA. "A NON-PARAMETRIC TRAINABLE OBJECT-DETECTION MODEL USING A CONCEPT OF RETINOTOPIC SAMPLING." International Journal of Computational Intelligence and Applications 04, no. 02 (2004): 115–30. http://dx.doi.org/10.1142/s1469026804001185.
Full textAbstract:
A retina has a space-variant sampling mechanism and an orientation-sensitive mechanism. The space-variant sampling mechanism of the retina is called Retinotopic Sampling (RS). With these mechanisms, the object-detection is formulated as finding an appropriate coordinate transformation from a coordinate system on the input image to the retina. The appropriate coordinate transformation is found using maximum likelihood method. By using the model based on RS, we formulate a kernel function as an analytical function of the information on the input image, the position and the size of the object in the input image. Then the object-detection is realised as a gradient decent method for a discriminant function trained by Support Vector Machine (SVM). This detection mechanism realises faster detection than exploring a visual scene in raster-like fashion. The discriminant function outperforms results of SVMs using a kernel function using intensities of all pixels (based on independently published results), in face detection experiments over test images in the MIT-CBCL face database.
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Zhao, Binglei, Chuan Zhu, and Sergio Della Sala. "Which properties of the visual stimuli predict the type of representation used in mental rotation?" Quarterly Journal of Experimental Psychology 72, no. 10 (2019): 2462–73. http://dx.doi.org/10.1177/1747021819846832.
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Two modes of internal representation, holistic and piecemeal transformation, have been reported as a means to perform mental rotation (MR) tasks. The stimulus complexity effect has been proposed as an indicator to disentangle between these two representation types. However, the complexity effect has not been fully confirmed owing to the fact that different performances could result from different types of stimuli. Moreover, whether the non-mirror foils play a role in forcing participants to encode all the information from the stimuli in MR tasks is still under debate. This study aims at testing the association between these two common types of representation with different stimuli in MR tasks. First, the numbers of segments and vertices in polygon stimuli were manipulated to test which property of the visual stimuli is more likely to influence the representation in MR tasks. Second, the role of non-mirror foils was examined by comparing the stimulus complexity effect in both with- and without-non-mirror foils conditions. The results revealed that the segment number affected the slope of the linear function relating response times to rotation angle, but the vertex number in the polygons did not. This suggests that a holistic representation was more likely to be adopted in processing integrated objects, whereas a piecemeal transformation was at play in processing multi-part objects. In addition, the stimulus complexity effect was observed in the with-non-mirror foils condition but not in the without-non-mirror foils one, providing a direct evidence to support the role of non-mirror foils in MR tasks.
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Han, Youkyung, Jaewan Choi, Jinha Jung, Anjin Chang, Sungchan Oh, and Junho Yeom. "Automated Coregistration of Multisensor Orthophotos Generated from Unmanned Aerial Vehicle Platforms." Journal of Sensors 2019 (April 14, 2019): 1–10. http://dx.doi.org/10.1155/2019/2962734.
Full textAbstract:
Image coregistration is a key preprocessing step to ensure the effective application of very-high-resolution (VHR) orthophotos generated from multisensor images acquired from unmanned aerial vehicle (UAV) platforms. The most accurate method to align an orthophoto is the installation of air-photo targets at a test site prior to flight image acquisition, and these targets were used as ground control points (GCPs) for georeferencing and georectification. However, there are time and cost limitations related to installing the targets and conducting field surveys on the targets during every flight. To address this problem, this paper presents an automated coregistration approach for orthophotos generated from VHR images acquired from multisensors mounted on UAV platforms. Spatial information from the orthophotos, provided by the global navigation satellite system (GNSS) at each image’s acquisition time, is used as ancillary information for phase correlation-based coregistration. A transformation function between the multisensor orthophotos is then estimated based on conjugate points (CPs), which are locally extracted over orthophotos using the phase correlation approach. Two multisensor datasets are constructed to evaluate the proposed approach. These visual and quantitative evaluations confirm the superiority of the proposed method.
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Mezzino, D., L. Chan, M. Santana Quintero, et al. "BUILT HERITAGE DOCUMENTATION AND MANAGEMENT: AN INTEGRATED CONSERVATION APPROACH IN BAGAN." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W2 (August 16, 2017): 143–50. http://dx.doi.org/10.5194/isprs-annals-iv-2-w2-143-2017.
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Good practices in heritage conservation are based on accurate information about conditions, materials, and transformation of built heritage sites. Therefore, heritage site documentation and its analysis are essential parts for their conservation. In addition, the devastating effects of recent catastrophic events in different geographical areas have highly affected cultural heritage places. Such areas include and are not limited to South Europe, South East Asia, and Central America. Within this framework, appropriate acquisition of information can effectively provide tools for the decision-making process and management. Heritage documentation is growing in innovation, providing dynamic opportunities for effectively responding to the alarming rate of destruction by natural events, conflicts, and negligence. In line with these considerations, a multidisciplinary team – including students and faculty members from Carleton University and Yangon Technological University, as well as staff from the Department of Archaeology, National Museum and Library (DoA) and professionals from the CyArk foundation – developed a coordinated strategy to document four temples in the site of Bagan (Myanmar). On-field work included capacity-building activities to train local emerging professionals in the heritage field (graduate and undergraduate students from the Yangon Technological University) and to increase the technical knowledge of the local DoA staff in the digital documentation field. Due to the short time of the on-field activity and the need to record several monuments, a variety of documentation techniques, including image and non-image based ones, were used. Afterwards, the information acquired during the fieldwork was processed to develop a solid base for the conservation and monitoring of the four documented temples. The relevance of developing this kind of documentation in Bagan is related to the vulnerability of the site, often affected by natural seismic events and flooding, as well as the lack of maintenance. Bagan provided an excellent case study to test the effectiveness of the proposed approach, to prevent and manage the damages of catastrophic events, and to support retrofitting actions. In order to test the flexibility of adopted methodology and workflow, temples with different features – in terms of architectural design, shape, and geometry – were selected. The goals of these documentation activities range from testing digital documentation workflows for the metric and visual recording of the site (reviewing strengths and limitations of particular recording techniques), to the definition of effective conditions assessment strategies.
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Zhou, Zhigang, and Jun Ling. "Calculation Method for Grading Size and Grading Bounding Box of Virtual Aggregate Based on DEM." Mathematical Problems in Engineering 2021 (June 25, 2021): 1–12. http://dx.doi.org/10.1155/2021/6659285.
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The grading size, which can be defined as the side length of the smallest square hole through which an aggregate with irregular shape can directly pass, is an important morphology parameter and can be used to calculate the gradation of mixture material. The grading bounding box, which can be defined as the circumscribed cuboid with central axis length being the grading size, is an important visual tool for observing the size and direction of the aggregate. Virtual test to calculate the grading size of a virtual aggregate is environmentally friendly and efficient, but the result provided by current research is imprecise and the grading bounding box is also rarely mentioned. In this paper, the multilevel complete projection algorithm is proposed to precisely calculate the grading size of a virtual aggregate. The whole process of the algorithm can be expressed by formula after the operation of sphere discretization by converting the virtual aggregate shell into the discrete aggregate. Then, the discrete aggregate is projected onto a complete series of the plane to form several 2D figures, and then, each 2D figure is projected onto a complete series of the orthogonal axis to form orthogonal segments. The grading size can finally be obtained by comparing the length of the above orthogonal segments based on the key central axis length principle. The influencing factors of computational accuracy and efficiency are considered in the algorithm. Finally, the grading bounding box can be built by using the Rodrigues transformation according to the information obtained from the above algorithm.
Dissertations / Theses on the topic "Field's Visual Information Transformation Test"
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Zirngast, Wendy Margaret, and n/a. "The relationship of drawing skills to visual perceptual abilities in year 7 students." University of Canberra. Education, 1987. http://erl.canberra.edu.au./public/adt-AUC20061112.123539.
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The aim of this field study was to investigate
the relationship between visual perceptual processes
and drawing ability in Year 7 students in the
Australian Capital Territory.
A random sample of five classes from five High
Schools, consisting of 113 year 7 students, was tested
for their ability in representational and memory
drawing, and a sample of good drawers was chosen by a
panel of five Independent judges.
The drawing ability of the "Good" Drawers Sample
was tested by means of Field's Visual Information
Transformation Test (VIT), and the visual perceptual
processes were tested using MacGregor's Perceptual
Index.(MPI) A statistical analysis of the ranked
scores was made using the Kruskal Wallis Analysis of
Variance, the Spearman Rho rank order correlation, and
the Mann Whitney U Test.
Conference papers on the topic "Field's Visual Information Transformation Test"
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Williams, Christopher B., John Gero, Yoon Lee, and Marie Paretti. "Exploring Spatial Reasoning Ability and Design Cognition in Undergraduate Engineering Students." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28925.
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This paper presents preliminary results from the first phase of a longitudinal study of design cognition and the effects of design education on design practice. The study aims to monitor the development of engineering design thinking through a three-year protocol study of control and experimental groups of engineering students. Using innovations in cognitive science that include ontologically-based coding of protocols and new methods of protocol analysis, the study is intended to characterize students’ cognitive development, identify differences over time, and relate those differences to students’ educational experiences. The first phase of this study focuses on assessing students’ spatial reasoning ability. Spatial reasoning is the ability to process and form ideas through spatial relationships among objects. It has been found to correlate strongly with the design ability associated with one’s ability to generate, conceptualize, and communicate solutions to problems. Sophomore students entering two different majors took four spatial reasoning tests (Paper Folding, Vandenberg, Mental Rotation, and Spatial Imagery Ability) that addressed their ability to visualize objects and mentally manipulate them over an ordered sequence of spatial transformations. The results of these tests are presented in this paper. Tests were conducted to determine statistical significance in order to evaluate whether a student’s spatial reasoning ability correlates with their choice of engineering major. The students’ test performances are also compared with existing data from other fields (e.g., architecture, visual arts, science, and humanities).
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Bernier, Edgar, and Sebastien Perrier. "Natural Language Processing and Text Mining Approaches in Production Shortfalls Analytics: Methodology, Case-Study and Value in the North Sea." In SPE Offshore Europe Conference & Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205443-ms.
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Abstract Maximizing operational efficiency is a critical challenge in oil and gas production, particularly important for mature assets in the North Sea. The causes of production shortfalls are numerous, distributed across a wide range of disciplines, technical and non-technical causes. The primary reason to apply Natural Language Processing (NLP) and text mining on several years of shortfall history was the need to support efficiently the evaluation of digital transformation use-case screenings and value mapping exercises, through a proper mapping of the issues faced. Obviously, this mapping contributed as well to reflect on operational surveillance and maintenance strategies to reduce the production shortfalls. This paper presents a methodology where the historical records of descriptions, comments and results of investigation regarding production shortfalls are revisited, adding to existing shortfall classifications and statistics, in particular in two domains: richer first root-cause mapping, and a series of advanced visualizations and analytics. The methodology put in place uses natural-language pre-processing techniques, combined with keyword-based text-mining and classification techniques. The limitations associated to the size and quality of these language datasets will be described, and the results discussed, highlighting the value of reaching high level of data granularity while defeating the ‘more information, less attention’ bias. At the same time, visual designs are introduced to display efficiently the different dimensions of this data (impact, frequency evolution through time, location in term of field and affected systems, root causes and other cause-related categories). The ambition in the domain of visualization is to create User Experience-friendly shortfall analytics, that can be displayed in smart rooms and collaborative rooms, where display's efficiency is higher when user-interactions are kept minimal, number of charts is limited and multiple dimensions do not collide. The paper is based on several applications across the North Sea. This case study and the associated lessons learned regarding natural language processing and text mining applied to similar technical concise data are answering several frequently asked questions on the value of the textual data records gathered over years.
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Venugopal, Kalyanaraman, Dvijesh Shastri, Suryanarayanan Radhakrishnan, and Ramanan Krishnamoorti. "An Online Microcredential Certification Program to Upskill Petrotechnical Professionals in Data Analytics and Machine Learning with an Upstream Oil and Gas Industry Focus." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205921-ms.
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Abstract The upstream oil and gas industry's digital transformation over the last few years has accelerated because of the COVID-19 pandemic. Data analytics and machine learning are key components of this digital transformation and have become essential skills for experienced petrotechnical professionals (PTPs) and aspiring entrants into the field. The objective of our work was to design and deliver a practical, engaging, and online microcredential certification program in upstream energy data analytics for PTPs. The program was conceived as a collaboration between academia (University of Houston's UH Energy) and industry (NExT, a Schlumberger company). It was designed as three belt levels (Bronze, Silver, and Gold), each containing three stackable badges of 12 to 15 hours duration per badge. Key design points included Identifying an online platform for administration Delivering convenient, interactive, live online sessions Delivering hybrid classes blending lectures and hands-on laboratories Designing laboratories using upstream datasets across various stages of oilfield expertise Administering test and quizzes, Kaggle competitions, and team projects. The program contents were designed incorporating appropriate instructional design practices for effective online class delivery. The design and delivery of the laboratories using a code-free approach by leveraging visual programming offers PTPs and new entrants a unique opportunity to learn data analytics concepts without the traditional concern of learning to code. Additionally, the collaboration between academia and industry enables delivering a program that combines academic rigor with application of the skills and knowledge to solve problems facing the industry using the real-world datasets. As a pilot program, all three badges of the Bronze belt were scheduled and successfully delivered during July and August 2020, as six 2-hour sessions per badge. From a total of 26 students registered in badge 1, 24 completed it, resulting in a completion rate of 92%. Out of these students, 19 registered and completed badge 2 and badge 3, resulting in the completion rates of 100%. Based on the success of the pilot program, a second delivery of the Bronze belt with 18 participants was offered from October 2020 through January 2021. All 18 participants completed all three badges. Feedback from participants attests to the success of the pilot program as seen in the following excerpts: "A very good course and instructors. I have already recommended the course to a friend and I will continue to be an advocate for the course." "Teachers are very receptive to questions and it is a joy to hear their lectures." "I found the University of Houston course to be both highly engaging and incredibly informative. The course teaches basic principles of data science without being bogged down by the specific coding language."
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Cho, Uichung, Kristin L. Wood, and Richard H. Crawford. "Novel Empirical Similarity Method for the Reliable Product Test With Rapid Prototypes." In ASME 1998 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/detc98/dac-5605.
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Abstract Contemporary industries are devoting increasing attention to the product development process, due to tight market shares and the abridged product life cycle. Reliable scaled product testing with rapid prototypes has the potential to improve these processes by replacing traditional costly and time-consuming product tests. In this context, rapid prototypes provide visual, ergonomic, and functional information with minimal time delay. Among the information classes, reliable functional information is least realized because of several features of rapid prototypes: (1) limited material choices and part size; (2) distinct material structure; (3) restrictive loading conditions; and (4) state-dependent material properties. To develop reliable functional tests, an improved similarity method is needed to overcome these limitations. The traditional similarity method, based on a Buckingham П approach, is commonly applied to perform scaled tests. In contrast to this method, wherein the state transformation between two similar systems is derived from dimensional vectors, we present a new similarity method that empirically derives the transformation from a geometrically simple specimen pair. The primary advantage of the new method over the traditional method is the capability to relate highly distorted systems. In this paper, the concept and theoretical framework of the novel similarity method are introduced, and two numerical examples demonstrate the new method.