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Variational maximum a posteriori by annealed mean field analysis

Gan, Ying Wu
2005 IEEE Transactions on Pattern Analysis and Machine Intelligence  
This paper proposes a novel probabilistic variational method with deterministic annealing for the maximum a posteriori (MAP) estimation of complex stochastic systems.  ...  Murphy Fellowship for Gang Hua.  ...  ACKNOWLEDGMENTS This work was supported in part by US National Science Foundation Grants IIS-0347877, IIS-0308222, and Northwestern faculty startup funds for Ying Wu and Walter P.  ... 
doi:10.1109/tpami.2005.229 pmid:16285374 fatcat:4b2oontrmvc4hckvazwbjfkpn4

Integrated Detection and Tracking for Multiple Moving Objects using Data-Driven MCMC Data Association

Qian Yu, Gerard Medioni
2008 2008 IEEE Workshop on Motion and video Computing  
To avoid enumerating all possible joint associations, we take a Data Driven Markov Chain Monte Carlo (DD-MCMC) approach which samples the solution space efficiently.  ...  Tracks are generated from these candidates according to the smoothness of motion, appearance and model likelihood overtime.  ...  Markov Chain Monte Carlo has been successfully applied in solving the data association problem in many areas, such as structure from motion [11] and multiple object tracking [12, 13] .  ... 
doi:10.1109/wmvc.2008.4544066 fatcat:kgtf3gj2uzhe7glm2vkc52mlkm

Multiple-Target Tracking by Spatiotemporal Monte Carlo Markov Chain Data Association

Qian Yu, G. Medioni
2009 IEEE Transactions on Pattern Analysis and Machine Intelligence  
To avoid enumerating all possible solutions, we take a Data-Driven Markov Chain Monte Carlo (DD-MCMC) approach to sample the solution space efficiently.  ...  We propose a framework for tracking multiple targets, where the input is a set of candidate regions in each frame, as obtained from a state-of-the-art background segmentation module, and the goal is to  ...  Due to the high computational complexity of such an association scheme, a Data-Driven Markov Chain Monte Carlo (DD-MCMC) [18] method is proposed to sample the solution space.  ... 
doi:10.1109/tpami.2008.253 pmid:19834141 fatcat:hzedmgfyajgorip4svlm54e43i

3D Human Motion Tracking with a Coordinated Mixture of Factor Analyzers

Rui Li, Tai-Peng Tian, Stan Sclaroff, Ming-Hsuan Yang
2009 International Journal of Computer Vision  
A major challenge in applying Bayesian tracking methods for tracking 3D human body pose is the high dimensionality of the pose state space.  ...  The advantages of the proposed model are demonstrated in a multiple hypothesis tracker for tracking 3D human body pose.  ...  We use GPLVMPF to refer this tracking algorithm. APF and GPLVMPF are chosen for comparison as both address the issue of sample impoverishment problem for particle filtering in 3D human tracking.  ... 
doi:10.1007/s11263-009-0283-4 fatcat:vnld2yq6w5ee7eh7ujondzzeiu

Human tracking over camera networks: a review

Li Hou, Wanggen Wan, Jenq-Neng Hwang, Rizwan Muhammad, Mingyang Yang, Kang Han
2017 EURASIP Journal on Advances in Signal Processing  
Two important functional modules for the human tracking over camera networks are addressed, including human tracking within a camera and human tracking across nonoverlapping cameras.  ...  In recent years, automated human tracking over camera networks is getting essential for video surveillance.  ...  The Markov Chain Monte Carlo (MCMC) method, which samples from a probability distribution based on constructing a Markov chain that has the desired distribution as its equilibrium distribution, is well  ... 
doi:10.1186/s13634-017-0482-z fatcat:sc6y6mffn5hjzaawmnduamqpz4

Statistical Methods and Models for Video-Based Tracking, Modeling, and Recognition

Rama Chellappa
2009 Foundations and Trends® in Signal Processing  
Julian Besag's contributions to the development of spatial interaction models [16, 18] and Monte Carlo Markov chain techniques [17] are seminal.  ...  In particular, we illustrate the role of imaging, illumination, and motion constraints in classical vision problems such as tracking, structure from motion, metrology, activity analysis and recognition  ...  Bob Gray and Reviewer A for the thorough proofreading, and the painstakingly detailed review.  ... 
doi:10.1561/2000000007 fatcat:o5hmdnzbqvbdzjdu72jkojl5ya

Vision-Based Hand Gesture Recognition for Human-Computer Interaction [chapter]

Xenophon Zabulis, Haris Baltzakis, Antonis Argyros
2009 Human Factors and Ergonomics  
Carlo tracking technique.  ...  Particle filtering Particle filters have been utilized to track the position of hands and the configuration of fingers in dense visual clutter.  ... 
doi:10.1201/9781420064995-c34 fatcat:ethpj6kys5dpdjihszbkjgqewa

Cyclic articulated human motion tracking by sequential ancestral simulation

Cheng Chang, R. Ansari, A. Khokhar
Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.  
Such coupling is maintained in tracking through Ancestral Simulation (AS) and Markov potentials in a Sequential Monte Carlo tracking framework.  ...  This paper presents a novel technique for tracking cyclic human motion based on decomposing complex cyclic motion into components and maintaining coupling between components.  ...  Markov Chain Monte Carlo (MCMC) methods such as Gibbs sampling and Slice sampling [10] may be used to simulate the inference.  ... 
doi:10.1109/cvpr.2004.1315143 fatcat:aeegogroczggritlsnpa2khbyy

2019 Index IEEE Robotics and Automation Letters Vol. 4

2019 IEEE Robotics and Automation Letters  
., +, LRA April 2019 902-909 Particle filtering (numerical methods) Environment-Aware Multi-Target Tracking of Pedestrians.  ...  Kojima, A., +, LRA July 2019 2592-2598 Filtering HMFP-DBRNN: Real-Time Hand Motion Filtering and Prediction via Deep Bidirectional RNN.  ...  Permanent magnets Adaptive Dynamic Control for Magnetically Actuated Medical Robots.  ... 
doi:10.1109/lra.2019.2955867 fatcat:ckastwefh5chhamsravandtnx4

Stochastic-Biomechanic Modeling and Recognition of Human Movement Primitives, in Industry, Using Wearables

Brenda Elizabeth Olivas-Padilla, Sotiris Manitsaris, Dimitrios Menychtas, Alina Glushkova
2021 Sensors  
This work is based on the hypothesis that with these models, it is possible to forecast workers' posture and identify the joints contributing to the motion, which can later be used for ergonomic risk prevention  ...  Euler angles were used for training to avoid forecasting errors such as bone stretching and invalid skeleton configurations, which commonly occur with models trained with joint positions.  ...  These models represent the human body as a set of articulated links in a kinetic chain where joint torques and forces are calculated using anthropometric, postural, and hand load data [15] .  ... 
doi:10.3390/s21072497 pmid:33916681 pmcid:PMC8038416 fatcat:oe5wve26yvhtlep4jxm6qtu7eq

Mathematics of Human Motion: from Animation towards Simulation (A View form the Outside) [article]

A.I. Zhmakin
2011 arXiv   pre-print
Simulation of human motion is the subject of study in a number of disciplines: Biomechanics, Robotics, Computer Animation, Control Theory, Neurophysiology, Medicine, Ergonomics.  ...  Thus the author hopes that this view from the outside will be of some interest not only for the strangers like himself, but for those who are inside as well.  ...  There are two main approaches for human motion analysis: motion analysis involving human body parts and tracking of motion [2] .  ... 
arXiv:1102.4992v1 fatcat:vf63c7dtqfdsra562sxlb7uh2m

Tutorial Review of Bio-Inspired Approaches to Robotic Manipulation for Space Debris Salvage

Alex Ellery
2020 Biomimetics  
This models human manipulation capabilities as implemented by the cerebellum and muscles/joints respectively.  ...  This promises robust and adaptive manipulation for complex tasks in salvaging space debris.  ...  Acknowledgments: I would like to thank my PhD student Collins Ogundipe for crafting the uncredited diagrams. Conflicts of Interest: There are no conflicts of interest. Biomimetics 2020, 5, 19  ... 
doi:10.3390/biomimetics5020019 pmid:32408615 pmcid:PMC7345424 fatcat:vjw2nklwunevnn2apee6vkdjx4

On Human Robot Interaction using Multiple Modes [article]

Neha Baranwal
2018 arXiv   pre-print
Humanoid robots have apparently similar body structure like human beings. Due to their technical design, they are sharing the same workspace with humans.  ...  All these come under the field of human robot interaction (HRI). There are various modes like speech, gesture, behavior etc. through which human can interact with robots.  ...  First part of his work on visual tracking where he focuses on head poses and shoulder moments. For tracking these moments Particle Swarm optimization algorithm is applied.  ... 
arXiv:1811.07206v1 fatcat:jgzpy36mdvg6xa4ltxfd5pbzou

The Visual System's Internal Model of the World

Tai Sing Lee
2015 Proceedings of the IEEE  
We will argue for a unified theoretical framework for relating the internal models to the observed neural phenomena and mechanisms in the visual cortex. became a faculty member at Carnegie Mellon University  ...  ABSTRACT | The Bayesian paradigm has provided a useful conceptual theory for understanding perceptual computation in the brain.  ...  Sampling techniques such as Gibbs sampling and Markov chain Monte Carlo (MCMC) are used to estimate this distribution.  ... 
doi:10.1109/jproc.2015.2434601 pmid:26566294 pmcid:PMC4638327 fatcat:bun4vapgzvepzigoq2lzbid6ua

Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art [article]

Joel Janai, Fatma Güney, Aseem Behl, Andreas Geiger
2021 arXiv   pre-print
Our survey includes both the historically most relevant literature as well as the current state of the art on several specific topics, including recognition, reconstruction, motion estimation, tracking  ...  , scene understanding, and end-to-end learning for autonomous driving.  ...  [11] address this problem with a joint detection and articulated human pose tracking formulation.  ... 
arXiv:1704.05519v3 fatcat:xiintiarqjbfldheeg2hsydyra
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