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A Data-driven Approach for Human Pose Tracking Based on Spatio-temporal Pictorial Structure
[article]
2016
arXiv
pre-print
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In this paper, we present a data-driven approach for human pose tracking in video data. ...
We formulate the human pose tracking problem as a discrete optimization problem based on spatio-temporal pictorial structure model and solve this problem in a greedy framework very efficiently. ...
et al. [56] present a tracking method based on spatio-temporal context learning. ...
arXiv:1608.00199v1
fatcat:ynm65dtvpfgoxcbs46uawbqk74
Automatic Pose Tracking and Motion Transfer to Arbitrary 3D Characters
[chapter]
2015
Lecture Notes in Computer Science
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In order to reduce the ambiguity of the estimated 3D pose, a modified spatio-temporal constraint based algorithm is used for articulated gesture estimation across frames while maintaining temporal coherence ...
Our approach demonstrates promising performance on par with state-of-theart techniques. ...
Pose Estimation from Monocular
Pictorial Structures To achieve fully automatic 2D human pose tracking from a video, we start with the state-of-the-art mixture of parts detectors by representing the human ...
doi:10.1007/978-3-319-21978-3_56
fatcat:mcofjzkw7nhkrpcp2xauh7ydi4
Interactive activity recognition using pose-based spatio–temporal relation features and four-level Pachinko Allocation Model
2016
Information Sciences
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We propose a novel approach that permits to deeply understand complex personperson activities based on the knowledge coming from human pose analysis. ...
We validate our interaction recognition method on two practical data sets, the BIT-Interaction data set and the UT-Interaction data set. ...
Furthermore, a shape-based kernel for upper-body pose similarity and a leave-one-out loss function were developed in the learning phase. Building on a successful pictorial structures model, Tian et al ...
doi:10.1016/j.ins.2016.06.016
fatcat:xaesiv7qivdy7la53h2qmukk54
Special issue: Behaviours in video
2013
Neurocomputing
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Acknowledgement The Guest Editors would like to thank all the authors for submitting their high quality manuscripts to this special issue, and all the reviewers for providing their timely review comments ...
Vera Kamphuis for encouraging and supporting this special issue.
Guest Editors Huiyu Zhou, Ph.D. Yuan Yuan, Ph.D. Yingzi Du, Ph.D. Pingkun Yan, Ph.D. ...
Bouziane et al. presented a unified framework for human behavior recognition, using Markov spatio-temporal random walks on graph. ...
doi:10.1016/j.neucom.2012.04.018
fatcat:l7vob67pybev3dwscg6p5lqfhq
Monocular human pose tracking using multi frame part dynamics
2009
2009 Workshop on Motion and Video Computing (WMVC)
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We present a monte-carlo approximation of the body dynamics using spatio-temporal distributions over part tracks. ...
To obtain tracks that favor kinematically feasible body poses, we propose a novel "kinematically constrained" particle filtering approach which results in more accurate pose tracking than other stochastic ...
We present an approximation of the spatio-temporal volume of human pose dynamics using part tracks and proposed a principled approach to efficiently sample kinematically consistent part tracks. ...
doi:10.1109/wmvc.2009.5399247
fatcat:3sgwaous5zgqdfit4kzjrq77gq
Athlete Pose Estimation from Monocular TV Sports Footage
2013
2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops
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Belief-propagation over a spatio-temporal graph of candidate body part hypotheses is used to estimate a temporally consistent pose between key-frame constraints. ...
We propose an interactive modelbased generative approach for estimating the human pose in 2D from uncalibrated monocular video in unconstrained sports TV footage without any prior learning on motion captured ...
Acknowledgements: The authors would like to thank BBC R&D, Graham Thomas and Robert Dawes for supporting this research and providing data. ...
doi:10.1109/cvprw.2013.152
dblp:conf/cvpr/FastovetsGH13
fatcat:yjt27mouezek7fpqk4iafdjb3q
Author Index
2010
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
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Detecting and Parsing Architecture at City Scale from Range Data
Adaptive Pose Priors for Pictorial Structures
Talking Pictures: Temporal Grouping and Dialog-Supervised Person Recognition
Workshop ...
Discovering Spatio-Temporal Dependencies in Dynamic Scenes Tracking the Invisible: Learning Where the Object Might be A Hough Transform-Based Voting Framework for Action Recognition Finding Nemo: Deformable ...
doi:10.1109/cvpr.2010.5539913
fatcat:y6m5knstrzfyfin6jzusc42p54
Space-Time Representation of People Based on 3D Skeletal Data: A Review
[article]
2017
arXiv
pre-print
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Spatiotemporal human representation based on 3D visual perception data is a rapidly growing research area. ...
Based on the information sources, these representations can be broadly categorized into two groups based on RGB-D information or 3D skeleton data. ...
Black, Pose-conditioned joint angle limits for 3D hu-
3D pictorial structures for multiple human pose estimation, in: IEEE man pose reconstruction, in: IEEE Conference on Computer Vision ...
arXiv:1601.01006v3
fatcat:zgpmw3xqunajtctu4e7minjyx4
Action is in the Eye of the Beholder: Eye-gaze Driven Model for Spatio-Temporal Action Localization
2013
Neural Information Processing Systems
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We propose a weakly-supervised structured learning approach for recognition and spatio-temporal localization of actions in video. ...
As part of the proposed approach, we develop a generalization of the Max-Path search algorithm which allows us to efficiently search over a structured space of multiple spatio-temporal paths while also ...
In [7] an extension to multiple sub-volumes that model parts of the action is proposed and amounts to a spatio-temporal part-based (pictorial structure) model. ...
dblp:conf/nips/ShapovalovaRSM13
fatcat:eoczf3q77vbplnyrsew7xaxt5y
Custom Pictorial Structures for Re-identification
2011
Procedings of the British Machine Vision Conference 2011
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We propose a novel methodology for re-identification, based on Pictorial Structures (PS). ...
It is based on the statistical learning of pixel attributes collected through spatio-temporal reasoning. ...
In this paper, we present a novel methodology for human re-id, based on Pictorial Structures (PS) for human body pose estimation. ...
doi:10.5244/c.25.68
dblp:conf/bmvc/ChengCSBM11
fatcat:hmdnnkst4jhv7e4tybzdttd2rm
A survey of advances in vision-based human motion capture and analysis
2006
Computer Vision and Image Understanding
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A number of significant research advances are identified together with novel methodologies for automatic initialization, tracking, pose estimation and movement recognition. ...
This survey reviews recent trends in video based human capture and analysis, as well as discussing open problems for future research to achieve automatic visual analysis of human movement. ...
Moeslund and Granum [205,211] apply a data driven sequential Monte Carlo approach to pose estimation of a human arm. ...
doi:10.1016/j.cviu.2006.08.002
fatcat:7vsbfnczrzgsbdbbmlzvfprh54
A Survey on Visual Surveillance of Object Motion and Behaviors
2004
IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)
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Visual surveillance in dynamic scenes, especially for humans and vehicles, is currently one of the most active research topics in computer vision. ...
and description of behaviors, human identification, and fusion of data from multiple cameras. ...
Xu from the NLPR for their valuable suggestions and assistance in preparing this paper. ...
doi:10.1109/tsmcc.2004.829274
fatcat:cozxn2ogtrew3pybyuxcrj2rhi
Recent Advances in Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective
[article]
2021
arXiv
pre-print
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We believe this survey will provide the readers with a deep and insightful understanding of monocular human pose estimation. ...
Estimation of the human pose from a monocular camera has been an emerging research topic in the computer vision community with many applications. ...
Moreover, instead of the manually defined body structure relation, they propose a data-driven approach to group related parts based on the amount of information they shared. ...
arXiv:2104.11536v1
fatcat:tdag2jq2vjdrjekwukm5nu7l6a
Video based activity recognition in trauma resuscitation
2013
2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)
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In this multi-agent, multitask setting, we represent procedures as high-level concepts composed of low-level features based on the patient's pose, scene dynamics, clinician motions and device locations ...
At runtime, a Markov Network is dynamically constructed representing hypothesized procedures, spatio-temporal relationships and attribute probabilities. ...
In this method, a weak human body detector identifies possible body locations followed by a stronger pictorial structure based model that enforces kinematic constraints on body parts. ...
doi:10.1109/fg.2013.6553758
dblp:conf/fgr/ChakrabortyEB13
fatcat:2ug24mlhkbggddsrbago2sqfwi
Recent Advances of Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective
2022
ACM Computing Surveys
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Estimation of the human pose from a monocular camera has been an emerging research topic in the computer vision community with many applications. ...
Then we summarize the mainstream and milestone approaches for these human body presentations since the year 2014 under unified frameworks. ...
Instead of using the shared features for all body parts, Tang et al. [192] propose a data-driven approach to group related parts based on the amount of information they shared. ...
doi:10.1145/3524497
fatcat:4pbvntngrnfp7lqhcpjmy7p2fq
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