Log in

Relevant bibliographies by topics / Human action recognition / Dissertations / Theses

To see the other types of publications on this topic, follow the link: Human action recognition.

Dissertations / Theses on the topic 'Human action recognition'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 dissertations / theses for your research on the topic 'Human action recognition.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.

1

Oshin, Olusegun Temitope. "Human action recognition from relative motion." Thesis, University of Surrey, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.549656.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Stefic, Daria. "Learning saliency for human action recognition." Thesis, Queen Mary, University of London, 2016. http://qmro.qmul.ac.uk/xmlui/handle/123456789/23656.

Full text

Abstract:

When we are looking at a visual stimuli, there are certain areas that stand out from the neighbouring areas and immediately grab our attention. A map that identi- es such areas is called a visual saliency map. As humans can easily recognize actions when watching videos, having their saliency maps available might be bene cial for a fully automated action recognition system. In this thesis we look into ways of learning to predict the visual saliency and how to use the learned saliency for action recognition. In the rst phase, as opposed to the approaches that use manually designed fea- tures for

APA, Harvard, Vancouver, ISO, and other styles

3

Liu, Chang. "Human motion detection and action recognition." HKBU Institutional Repository, 2010. http://repository.hkbu.edu.hk/etd_ra/1108.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Umakanthan, Sabanadesan. "Human action recognition from video sequences." Thesis, Queensland University of Technology, 2016. https://eprints.qut.edu.au/93749/1/Sabanadesan_Umakanthan_Thesis.pdf.

Full text

Abstract:

This PhD research has proposed new machine learning techniques to improve human action recognition based on local features. Several novel video representation and classification techniques have been proposed to increase the performance with lower computational complexity. The major contributions are the construction of new feature representation techniques, based on advanced machine learning techniques such as multiple instance dictionary learning, Latent Dirichlet Allocation (LDA) and Sparse coding. A Binary-tree based classification technique was also proposed to deal with large amounts of a

APA, Harvard, Vancouver, ISO, and other styles

5

Chakraborty, Bhaskar. "Model free approach towards human action recognition." Doctoral thesis, Universitat Autònoma de Barcelona, 2012. http://hdl.handle.net/10803/117657.

Full text

Abstract:

La comprensio automatica de les accions humanes observades en sequencies d'imatges es molt important en el area de recerca de la Vision per Computador, amb aplicacions a gran escala en la vigilancia de video, analisi del moviment huma, interficies de realitat virtual, robots de navegacio, aixi com per al reconeixement, indexacio, i recuperacio de video. Aquesta tesi presenta una serie de tecniques per resoldre el problema del reconeixement de les accions humanes en video. El nostre primer enfocament cap a aquesta tema es basa en la optimitzacio d'un model probabilistic de les parts del co

APA, Harvard, Vancouver, ISO, and other styles

6

Wang, Xuelu. "Human Action Recognition from Gradient Boundary Histograms." Thesis, Université d'Ottawa / University of Ottawa, 2017. http://hdl.handle.net/10393/35931.

Full text

Abstract:

This thesis presents a framework for automatic recognition of human actions in un- controlled, realistic video data with fixed cameras, such as surveillance videos. In this thesis, we divide human action recognition into three steps: description, representation, and classification of local spatio-temporal features. The bag-of-features model was used to build the classifier. Fisher Vectors were also studied. We focus on the potential of the methods, with the joint optimization of two constraints: the classification precision and its efficiency. On the performance side, a new local descriptor,

APA, Harvard, Vancouver, ISO, and other styles

7

Mejia, Maria Helena. "Human Action Recognition on Videos: Different Approaches." Diss., The University of Arizona, 2012. http://hdl.handle.net/10150/265361.

Full text

Abstract:

The goal of human action recognition on videos is to determine in an automatic way what is happening in a video. This work focuses on providing an answer to this question: given consecutive frames from a video where a person or persons are doing an action, is an automatic system able to recognize the action that is going on for each person? Seven approaches have been provided, most of them based on an alignment process in order to find a measure of distance or similarity for obtaining the classification. Some are based on fluents that are converted to qualitative sequences of Allen relations t

APA, Harvard, Vancouver, ISO, and other styles

8

Megrhi, Sameh. "Spatio-temporal descriptors for human action recognition." Thesis, Paris 13, 2014. http://www.theses.fr/2014PA131046/document.

Full text

Abstract:

L'analyse et l’interprétation de contenus visuels et plus particulièrement la vidéo est un domaine de recherche de plus en plus attractif en raison du nombre important d'applications telles que la vidéo-surveillance, le résumé de films, l'indexation, les jeux vidéo, la robotique et la domotique. Dans cette thèse nous nous intéressons à la détection et à la reconnaissance d'actions humaines dans des séquences vidéo. Pour la partie détection des actions, nous avons introduit deux approches basées sur les points d'intérêts locaux. La première proposition est une méthode simple et efficace qui vis

APA, Harvard, Vancouver, ISO, and other styles

9

Carmona, Leyva Josep Maria. "A template based approach for human action recognition." Doctoral thesis, Universitat Politècnica de Catalunya, 2018. http://hdl.handle.net/10803/619801.

Full text

Abstract:

Visual analysis of human movements concerns the understanding of human activities from image sequences. The goal of the action/gesture recognition is to recognize the label that corresponds to an action or gesture made by a human in a sequence of images. To solve this problem, the researchers have proposed solutions that range from object recognition techniques, to speech recognition techniques, face recognition or brain function . The techniques presented in this thesis, are related to a set of techniques that condense a video sequence into a template that retain important information to ac

APA, Harvard, Vancouver, ISO, and other styles

10

Boyraz, Hakan. "Human Action Localization and Recognition in Unconstrained Videos." Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5910.

Full text

Abstract:

As imaging systems become ubiquitous, the ability to recognize human actions is becoming increasingly important. Just as in the object detection and recognition literature, action recognition can be roughly divided into classification tasks, where the goal is to classify a video according to the action depicted in the video, and detection tasks, where the goal is to detect and localize a human performing a particular action. A growing literature is demonstrating the benefits of localizing discriminative sub-regions of images and videos when performing recognition tasks. In this thesis, we addr

APA, Harvard, Vancouver, ISO, and other styles

11

Cronje, Frans. "Human action recognition with 3D convolutional neural networks." Master's thesis, University of Cape Town, 2015. http://hdl.handle.net/11427/15482.

Full text

Abstract:

Convolutional neural networks (CNNs) adapt the regular fully-connected neural network (NN) algorithm to facilitate image classification. Recently, CNNs have been demonstrated to provide superior performance across numerous image classification databases including large natural images (Krizhevsky et al., 2012). Furthermore, CNNs are more readily transferable between different image classification problems when compared to common alternatives. The extension of CNNs to video classification is simple and the rationale behind the components of the model are still applicable due to the similarity be

APA, Harvard, Vancouver, ISO, and other styles

12

Youssef, Menatoallah M. "Hull Convexity Defect Features for Human Action Recognition." University of Dayton / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1312225825.

Full text

APA, Harvard, Vancouver, ISO, and other styles

13

Wu, Di. "Human action recognition using deep probabilistic graphical models." Thesis, University of Sheffield, 2014. http://etheses.whiterose.ac.uk/6603/.

Full text

Abstract:

Building intelligent systems that are capable of representing or extracting high-level representations from high-dimensional sensory data lies at the core of solving many A.I. related tasks. Human action recognition is an important topic in computer vision that lies in high-dimensional space. Its applications include robotics, video surveillance, human-computer interaction, user interface design, and multi-media video retrieval amongst others. A number of approaches have been proposed to extract representative features from high-dimensional temporal data, most commonly hard wired geometric or

APA, Harvard, Vancouver, ISO, and other styles

14

Zhen, Xiantong. "Feature extraction and representation for human action recognition." Thesis, University of Sheffield, 2013. http://etheses.whiterose.ac.uk/5141/.

Full text

Abstract:

Human action recognition, as one of the most important topics in computer vision, has been extensively researched during the last decades; however, it is still regarded as a challenging task especially in realistic scenarios. The difficulties mainly result from the huge intra-class variation, background clutter, occlusions, illumination changes and noise. In this thesis, we aim to enhance human action recognition by feature extraction and representation using both holistic and local methods. Specifically, we have first proposed three approaches for the holistic representation of actions. In th

APA, Harvard, Vancouver, ISO, and other styles

15

Rezazadegan, Fahimeh. "Human action recognition and prediction for robotics applications." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/127283/1/__qut.edu.au_Documents_StaffHome_StaffGroupH%24_halla_Desktop_Fahimeh_Rezazadegan_Thesis.pdf.

Full text

Abstract:

This study is a step forward in developing two different methods; one recognises human actions in an unbiased environment, the other predicts the next human action. The proposed methods that are based on deep learning, convolutional neural networks and long-short term memories, work regardless of camera motion, viewpoint variation, and irrelevant background context. The key outcome of this research is to enable an assistive robot to help a human peer performing an assembly task, using the proposed algorithms.

APA, Harvard, Vancouver, ISO, and other styles

16

Palasek, Petar. "Action recognition using deep learning." Thesis, Queen Mary, University of London, 2017. http://qmro.qmul.ac.uk/xmlui/handle/123456789/30828.

Full text

Abstract:

In this thesis we study deep learning architectures for the problem of human action recognition in image sequences, i.e. the problem of automatically recognizing what people are doing in a given video. As unlabeled video data is easily accessible these days, we first explore models that can learn meaningful representations of sequences without actually having to know what is happening in the sequences at hand. More specifically, we first explore the convolutional restricted Boltzmann machine (RBM) and show how a stack of convolutional RBMs can be used to learn and extract features from sequenc

APA, Harvard, Vancouver, ISO, and other styles

17

Eweiwi, Abdalrahman [Verfasser]. "Human Motion Analysis for Efficient Action Recognition / Abdalrahman Eweiwi." Bonn : Universitäts- und Landesbibliothek Bonn, 2015. http://d-nb.info/1080561323/34.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

Weiss, Jan. "Speed-invariant video comparison for robust human action recognition." Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-60293.

Full text

Abstract:

As cameras and especially 3D cameras got affordable within recent years they can be used by a wider range of people. Human action recognition based on 3D coordinates recorded with such devices including a depth camera made it possible to compute video data easier. Many already published papers ignore the difference of speed within the execution of the same action. This paper suggests and evaluates multiple algorithms handling that problem based on Dynamic Time Warping and compares them with regard to runtime and accuracy. An additional algorithm from Softwerk AB is analyzed, adjusted and compa

APA, Harvard, Vancouver, ISO, and other styles

19

Ji, Xiaofei. "View-invariant Human Action Recognition via Probabilistic Graphical Models." Thesis, University of Portsmouth, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.523620.

Full text

APA, Harvard, Vancouver, ISO, and other styles

20

Moreira, Thierry Pinheiro 1990. "Real-time human action recognition based on motion shapes." [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/275509.

Full text

Abstract:

Orientador: Hélio Pedrini<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação<br>Made available in DSpace on 2018-08-25T12:27:06Z (GMT). No. of bitstreams: 1 Moreira_ThierryPinheiro_M.pdf: 1679150 bytes, checksum: 2bd22b1849bd7a34a85e6b5ba649bbf2 (MD5) Previous issue date: 2014<br>Resumo: Reconhecimento de ações humanas em vídeos é uma área de conhecimento em expansão. Há uma vasta gama de possíveis aplicações, incluindo interface de usuários, vigilância, casas inteligentes e monitoramento de saúde. A maioria delas requer respostas em tempo real. No entanto

APA, Harvard, Vancouver, ISO, and other styles

21

Bux, Allah. "Vision-based human action recognition using machine learning techniques." Thesis, Lancaster University, 2017. http://eprints.lancs.ac.uk/89205/.

Full text

Abstract:

The focus of this thesis is on automatic recognition of human actions in videos. Human action recognition is defined as automatic understating of what actions occur in a video performed by a human. This is a difficult problem due to the many challenges including, but not limited to, variations in human shape and motion, occlusion, cluttered background, moving cameras, illumination conditions, and viewpoint variations. To start with, The most popular and prominent state-of-the-art techniques are reviewed, evaluated, compared, and presented. Based on the literature review, these techniques are c

APA, Harvard, Vancouver, ISO, and other styles

22

Janse, Van Vuuren Michaella. "Human Pose and Action Recognition using Negative Space Analysis." Diss., University of Cape Town, 2004. http://hdl.handle.net/10919/71571.

Full text

Abstract:

This thesis proposes a novel approach to extracting pose information from image sequences. Current state of the art techniques focus exclusively on the image space occupied by the body for pose and action recognition. The method proposed here, however, focuses on the negative spaces: the areas surrounding the individual. This has resulted in the colour-coded negative space approach, an image preprocessing step that circumvents the need for complicated model fitting or template matching methods. The approach can be described as follows: negative spaces surrounding the human silhouette are extra

APA, Harvard, Vancouver, ISO, and other styles

23

Gurrapu, Chaitanya. "Human Action Recognition In Video Data For Surveillance Applications." Thesis, Queensland University of Technology, 2004. https://eprints.qut.edu.au/15878/1/Chaitanya_Gurrapu_Thesis.pdf.

Full text

Abstract:

Detecting human actions using a camera has many possible applications in the security industry. When a human performs an action, his/her body goes through a signature sequence of poses. To detect these pose changes and hence the activities performed, a pattern recogniser needs to be built into the video system. Due to the temporal nature of the patterns, Hidden Markov Models (HMM), used extensively in speech recognition, were investigated. Initially a gesture recognition system was built using novel features. These features were obtained by approximating the contour of the foreground object wi

APA, Harvard, Vancouver, ISO, and other styles

24

Gurrapu, Chaitanya. "Human Action Recognition In Video Data For Surveillance Applications." Queensland University of Technology, 2004. http://eprints.qut.edu.au/15878/.

Full text

Abstract:

Detecting human actions using a camera has many possible applications in the security industry. When a human performs an action, his/her body goes through a signature sequence of poses. To detect these pose changes and hence the activities performed, a pattern recogniser needs to be built into the video system. Due to the temporal nature of the patterns, Hidden Markov Models (HMM), used extensively in speech recognition, were investigated. Initially a gesture recognition system was built using novel features. These features were obtained by approximating the contour of the foreground object wi

APA, Harvard, Vancouver, ISO, and other styles

25

Gammulle, Pranali Harshala. "Deep learning for human action understanding." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/135199/1/Pranali_Gammulle_Thesis.pdf.

Full text

Abstract:

This thesis addresses the problem of understanding human behaviour in videos in multiple problem settings including, recognition, segmentation, and prediction. Considering the complex nature of human behaviour, we propose to capture both short-term and long-term context in the given videos and propose novel multitask learning-based approaches to solve the action prediction task, as well as an adversarially-trained approach to action recognition. We demonstrate the efficacy of these techniques by applying them to multiple real-world human behaviour understanding settings including, security sur

APA, Harvard, Vancouver, ISO, and other styles

26

GRITAI, ALEXEI. "MULTI-VIEW GEOMETRIC CONSTRAINTS FOR HUMAN ACTION RECOGNITION AND TRACKING." Doctoral diss., University of Central Florida, 2007. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4032.

Full text

Abstract:

Human actions are the essence of a human life and a natural product of the human mind. Analysis of human activities by a machine has attracted the attention of many researchers. This analysis is very important in a variety of domains including surveillance, video retrieval, human-computer interaction, athlete performance investigation, etc. This dissertation makes three major contributions to automatic analysis of human actions. First, we conjecture that the relationship between body joints of two actors in the same posture can be described by a 3D rigid transformation. This transformation sim

APA, Harvard, Vancouver, ISO, and other styles

27

Gong, Wenjuan. "3D Motion Data aided Human Action Recognition and Pose Estimation." Doctoral thesis, Universitat Autònoma de Barcelona, 2013. http://hdl.handle.net/10803/116189.

Full text

Abstract:

En aquest treball s’explora el reconeixement d’accions humanes i l'estimació de la seva postura en seqüències d'imatges. A diferència de les tècniques tradicionals d’aprenentatge a partir d’imatges 2D o vídeo amb la sortida anotada, en aquesta Tesi abordem aquest objectiu amb la informació de moviment 3D capturat, que ens ajudar a tancar el llaç entre les característiques 2D de la imatge i les interpretacions sobre el moviment humà.<br>En este trabajo se exploran el reconocimiento de acciones humanas y la estimación de su postura en secuencias de imágenes. A diferencia de las técnicas tradicio

APA, Harvard, Vancouver, ISO, and other styles

28

Sinai, Sam. "A study in human attention to guide computational action recognition." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/91871.

Full text

Abstract:

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 93-95).<br>Computer vision researchers have a lot to learn from the human visual system. We, as humans, are usually unaware of how enormously difficult it is to watch a scene and summarize its most important events in words. We only begin to appreciate this truth when we attempt to build a system that performs comparably. In this thesis, I study two features of human visual apparatus: Atte

APA, Harvard, Vancouver, ISO, and other styles

29

Abdulmunem, Ashwan. "Human action recognition using saliency-based global and local features." Thesis, Cardiff University, 2017. http://orca.cf.ac.uk/107750/.

Full text

Abstract:

Recognising human actions from video sequences is one of the most important topics in computer vision and has been extensively researched during the last decades; however, it is still regarded as a challenging task especially in real scenarios due to difficulties mainly resulting from background clutter, partial occlusion, as well as changes in scale, viewpoint, lighting, and appearance. Human action recognition is involved in many applications, including video surveillance systems, human-computer interaction, and robotics for human behaviour characterisation. In this thesis, we aim to introdu

APA, Harvard, Vancouver, ISO, and other styles

30

Chivers, Daniel Stephen. "Human Action Recognition by Principal Component Analysis of Motion Curves." Wright State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=wright1353374113.

Full text

APA, Harvard, Vancouver, ISO, and other styles

31

Leightley, Daniel. "3D human action recognition and motion analysis using selective representations." Thesis, Manchester Metropolitan University, 2015. http://e-space.mmu.ac.uk/600402/.

Full text

Abstract:

With the advent of marker-based motion capture, attempts have been made to recognise and quantify attributes of “type”, “content” and “behaviour” from the motion data. Current work exists to obtain quick and easy identification of human motion for use in multiple settings, such as healthcare and gaming by using activity monitors, wearable technology and low-cost accelerometers. Yet, analysing human motion and generating representative features to enable recognition and analysis in an efficient and comprehensive manner has proved elusive thus far. This thesis proposes practical solutions that a

APA, Harvard, Vancouver, ISO, and other styles

32

Hu, Kun. "Fine-grained Human Action Recognition for Freezing of Gait Detection." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/27286.

Full text

Abstract:

Freezing of gait (FoG) presents as a sudden and brief episode of movement cessation despite the intention to continue walking. As a common symptom of Parkinson's Disease, early detection and quantification of FoG are of great importance in clinical practice. Therefore, this thesis focuses on vision-based and pressure-based FoG detection methods, which were seldom investigated in the past. The task can be treated as a human action recognition problem. Although various deep architectures have achieved encouraging performance for general action recognition, FoG events contain fine-grained pattern

APA, Harvard, Vancouver, ISO, and other styles

33

Dogan, Emre. "Human pose estimation and action recognition by multi-robot systems." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSEI060/document.

Full text

Abstract:

L'estimation de la pose humaine et la reconnaissance des activités humaines sont des étapes importantes dans de nombreuses applications comme la robotique, la surveillance et la sécurité, etc. Actuellement abordées dans le domaine, ces tâches ne sont toujours pas résolues dans des environnements non-coopératifs particulièrement. Ces tâches admettent de divers défis comme l'occlusion, les variations des vêtements, etc. Les méthodes qui exploitent des images de profondeur ont l’avantage concernant les défis liés à l'arrière-plan et à l'apparence, pourtant, l’application est limitée pour des rais

APA, Harvard, Vancouver, ISO, and other styles

34

Magnani, Antonio <1988&gt. "Human Action Recognition and Monitoring in Ambient Assisted Living Environments." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amsdottorato.unibo.it/9373/1/Magnani_Antonio_PhDThesis.pdf.

Full text

Abstract:

Population ageing is set to become one of the most significant challenges of the 21st century, with implications for almost all sectors of society. Especially in developed countries, governments should immediately implement policies and solutions to facilitate the needs of an increasingly older population. Ambient Intelligence (AmI) and in particular the area of Ambient Assisted Living (AAL) offer a feasible response, allowing the creation of human-centric smart environments that are sensitive and responsive to the needs and behaviours of the user. In such a scenario, understand what a human

APA, Harvard, Vancouver, ISO, and other styles

35

AlBahar, Badour A. Sh A. "Im2Vid: Future Video Prediction for Static Image Action Recognition." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/83602.

Full text

Abstract:

Static image action recognition aims at identifying the action performed in a given image. Most existing static image action recognition approaches use high-level cues present in the image such as objects, object human interaction, or human pose to better capture the action performed. Unlike images, videos have temporal information that greatly improves action recognition by resolving potential ambiguity. We propose to leverage a large amount of readily available unlabeled videos to transfer the temporal information from video domain to static image domain and hence improve static image action

APA, Harvard, Vancouver, ISO, and other styles

36

Ciptadi, Arridhana. "Interactive tracking and action retrieval to support human behavior analysis." Diss., Georgia Institute of Technology, 2016. http://hdl.handle.net/1853/54987.

Full text

Abstract:

The goal of this thesis is to develop a set of tools for continuous tracking of behavioral phenomena in videos to support human behavior study. Current standard practices for extracting useful behavioral information from a video are typically difficult to replicate and require a lot of human time. For example, extensive training is typically required for a human coder to reliably code a particular behavior/interaction. Also, manual coding typically takes a lot more time than the actual length of the video (e.g. , it can take up to 6 times the actual length of the video to do human-assisted sin

APA, Harvard, Vancouver, ISO, and other styles

37

Hadfield, S. J. "The estimation and use of 3D information, for natural human action recognition." Thesis, University of Surrey, 2013. http://epubs.surrey.ac.uk/773425/.

Full text

Abstract:

The aim of this thesis, is to develop estimation and encoding techniques for 3D information, which are applicable in a range of vision tasks. Particular emphasis is given to the task of natural action recognition. This 'in the wild' recognition, favours algorithms with broad generalisation capabilities, as no constraints are placed on either the actor, or the setting. This leads to huge intra-class variability, including changes in lighting, actor appearance, viewpoint and action style. Algorithms which perform well under these circumstances, are generally well suited for real world deployment

APA, Harvard, Vancouver, ISO, and other styles

38

Ta, Anh Phuong. "Inexact graph matching techniques : application to object detection and human action recognition." Lyon, INSA, 2010. http://theses.insa-lyon.fr/publication/2010ISAL0099/these.pdf.

Full text

Abstract:

Object detection and human action recognition are two active fields of research in computer vision, which have applications ranging from robotics and video surveillance, medical image analysis, human-computer interactions to content-based video annotation and retrieval. At this time, building such robust recognition systems still remain very challenging tasks, because of the variations in action/object classes, different possible viewpoints, as well as illumination changes, moving cameras, complex dynamic backgrounds and occlusions. In this thesis, we deal with object and activity recognition

APA, Harvard, Vancouver, ISO, and other styles

39

Terzi, Matteo. "Learning interpretable representations for classification, anomaly detection, human gesture and action recognition." Doctoral thesis, Università degli studi di Padova, 2019. http://hdl.handle.net/11577/3423183.

Full text

Abstract:

The goal of this thesis is to provide algorithms and models for classification, gesture recognition and anomaly detection with a partial focus on human activity. In applications where humans are involved, it is of paramount importance to provide robust and understandable algorithms and models. A way to accomplish this requirement is to use relatively simple and robust approaches, especially when devices are resource-constrained. The second approach, when a large amount of data is present, is to adopt complex algorithms and models and make them robust and interpretable from a human-like point

APA, Harvard, Vancouver, ISO, and other styles

40

Kepenekci, Burcu. "Human Activity Recognition By Gait Analysis." Phd thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613089/index.pdf.

Full text

Abstract:

This thesis analyzes the human action recognition problem. Human actions are modeled as a time evolving temporal texture. Gabor filters, which are proved to be a robust 2D texture representation tool by detecting spatial points with high variation, is extended to 3D domain to capture motion texture features. A well known filtering algorithm and a recent unsupervised clustering algorithm, the Genetic Chromodynamics, are combined to select salient spatio-temporal features of the temporal texture and to segment the activity sequence into temporal texture primitives. Each activity sequence is repr

APA, Harvard, Vancouver, ISO, and other styles

41

de, Souza César Roberto. "Action recognition in videos: data-efficient approaches for supervised learning of human action classification models for video." Doctoral thesis, Universitat Autònoma de Barcelona, 2018. http://hdl.handle.net/10803/565827.

Full text

Abstract:

En aquesta dissertació, explorem diferents maneres de reconèixer accions humanes en fragments de vídeo. Ens centrem sobretot en l'eficiència amb les dades, investigant i proposant nous mètodes que permetin evitar la laboriosa i lenta anotació de dades de forma manual. A la primera part d'aquesta dissertació, comencem analitzem els millors models preexistents, comparant les seves diferències i similituds amb la finalitat d'identificar d'on provenen els seus punts forts. Aprofitant aquesta informació, procedim a millorar el rendiment en classificació d'aquests models senzills a nivells que podri

APA, Harvard, Vancouver, ISO, and other styles

42

Laptev, Ivan. "Modeling and visual recognition of human actions and interactions." Habilitation à diriger des recherches, Ecole Normale Supérieure de Paris - ENS Paris, 2013. http://tel.archives-ouvertes.fr/tel-01064540.

Full text

Abstract:

This work addresses the problem of recognizing actions and interactions in realistic video settings such as movies and consumer videos. The first contribution of this thesis (Chapters 2 and 4) is concerned with new video representations for action recognition. We introduce local space-time descriptors and demonstrate their potential to classify and localize actions in complex settings while circumventing the difficult intermediate steps of person detection, tracking and human pose estimation. The material on bag-of-features action recognition in Chapter 2 is based on publications [L14, L22, L2

APA, Harvard, Vancouver, ISO, and other styles

43

Isik, Leyla. "The dynamics of invariant object and action recognition in the human visual system." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98000.

Full text

Abstract:

Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2015.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 123-138).<br>Humans can quickly and effortlessly recognize objects, and people and their actions from complex visual inputs. Despite the ease with which the human brain solves this problem, the underlying computational steps have remained enigmatic. What makes object and action recognition challenging are identity-preserving transformations that alter the visual appearance of objects and actions, such as c

APA, Harvard, Vancouver, ISO, and other styles

44

Slama, Rim. "Geometric approaches for 3D human motion analysis : application to action recognition and retrieval." Thesis, Lille 1, 2014. http://www.theses.fr/2014LIL10078/document.

Full text

Abstract:

Dans le cadre de cette thèse, nous proposons des approches géométriques permettant d’analyser des mouvements humains à partir de données issues de capteurs 3D. Premièrement, nous abordons le problème de comparaison de poses et de mouvements dans des séquences contenant des modèles de corps humain en 3D. En introduisant un nouveau descripteur, appelé Extremal Human Curve (EHC), la forme du corps humain dans une pose donnée est décrite par une collection de courbes. Ces courbes extraites de la surface du maillage relient les points se situant aux extrémités du corps. Dans un formalisme Riemannie

APA, Harvard, Vancouver, ISO, and other styles

45

CIPPITELLI, Enea. "Human action recognition and mobility assessment in smart environments with RGB-D sensors." Doctoral thesis, Università Politecnica delle Marche, 2017. http://hdl.handle.net/11566/245464.

Full text

Abstract:

Questa attività di ricerca è focalizzata sullo sviluppo di algoritmi e soluzioni per ambienti intelligenti sfruttando sensori RGB e di profondità. In particolare, gli argomenti affrontati fanno riferimento alla valutazione della mobilità di un soggetto e al riconoscimento di azioni umane. Riguardo il primo tema, l'obiettivo è quello di implementare algoritmi per l'estrazione di parametri oggettivi che possano supportare la valutazione di test di mobilità svolta da personale sanitario. Il primo algoritmo proposto riguarda l'estrazione di sei joints sul piano sagittale utilizzando i dati di pro

APA, Harvard, Vancouver, ISO, and other styles

46

Chéron, Guilhem. "Structured modeling and recognition of human actions in video." Thesis, Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLEE058.

Full text

Abstract:

La compréhension automatique de vidéos devrait impacter notre vie de tous les jours dans de nombreux domaines comme la conduite autonome, les robots domestiques, la recherche et le filtrage de contenu, les jeux vidéo, la défense ou la sécurité. Le nombre de vidéos croît plus vite chaque année, notamment sur les plateformes telles que YouTube, Twitter ou Facebook. L’analyse automatique de ces données est indispensable pour permettre à de nouvelles applications de voir le jour. L’analyse vidéo, en particulier en environnement non contrôlé, se heurte à plusieurs problèmes comme la variabilité int

APA, Harvard, Vancouver, ISO, and other styles

47

Nagaraja, Adarsh. "Feature pruning for action recognition in complex environment." Master's thesis, University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4992.

Full text

Abstract:

A significant number of action recognition research efforts use spatio-temporal interest point detectors for feature extraction. Although the extracted features provide useful information for recognizing actions, a significant number of them contain irrelevant motion and background clutter. In many cases, the extracted features are included as is in the classification pipeline, and sophisticated noise removal techniques are subsequently used to alleviate their effect on classification. We introduce a new action database, created from the Weizmann database, that reveals a significant weakness i

APA, Harvard, Vancouver, ISO, and other styles

48

Kurt, Ugur Halis. "Anticipation of Human Movements : Analyzing Human Action and Intention: An Experimental Serious Game Approach." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15777.

Full text

Abstract:

What is the difference between intention and action? To start answering this complex question, we have created a serious game that allows us to capture a large quantity of experimental data and study human behavior. In the game, users catch flies, presented to the left or to the right of the screen, by dragging the tongue of a frog across a touchscreen monitor. The movement of interest has a predefined starting point (the frog) and necessarily transits through a via-point (a narrow corridor) before it proceeds to the chosen left/right direction. Meanwhile, the game collects data about the move

APA, Harvard, Vancouver, ISO, and other styles

49

Farrajota, Miguel. "Human pose and action recognition." Doctoral thesis, 2017. http://hdl.handle.net/10400.1/10809.

Full text

Abstract:

This thesis focuses on detection of persons and pose recognition using neural networks. The goal is to detect human body poses in a visual scene with multiple persons and to use this information in order to recognize human activity. This is achieved by rst detecting persons in a scene and then by estimating their body joints in order to infer articulated poses. The work developed in this thesis explored neural networks and deep learning methods. Deep learning allows to employ computational models that are composed of multiple processing layers to learn representations of data with mult

APA, Harvard, Vancouver, ISO, and other styles

50

DWIVEDI, AWANTIKA. "SILHOUETTE BASED HUMAN ACTION RECOGNITION." Thesis, 2017. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16096.

Full text

Abstract:

Human motion analysis is currently receiving increasing attention from computer vision researchers. This interest is motivated by applications over a wide spectrum of topics. For example, segmenting the parts of the human body in an image, tracking the movement of joints over an image sequence, and recovering the underlying 3D body structure are particularly useful for analysis of athletic performance, as well as medical diagnostics. The capability to automatically monitor human activities using computers in security-sensitive areas such as airports, border crossings, and building lobbies is o

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!