The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Nous proposons une approche nouvelle et efficace pour suivre les parties articulées du corps humain en 2D. Dans notre approche, le corps humain est modélisé par un modèle graphique où chaque partie est représentée par un nœud et la relation entre une paire de parties adjacentes est indiquée par une arête dans le graphique. Diverses approches ont été proposées pour résoudre ces problèmes, mais l’efficacité reste un problème vital. Nous présentons une nouvelle approche basée sur Quick Shift Belief Propagation (QSBP) qui bénéficie de Quick Shift, une méthode de recherche de mode simple et efficace, dans un modèle de propagation de croyance basé sur des parties. L'aspect unique de ce modèle est sa capacité à découvrir efficacement les modes de la distribution de probabilité marginale sous-jacente tout en préservant la précision. Cela donne au QSBP un avantage significatif par rapport aux approches telles que la propagation des croyances (BP) et la propagation des croyances moyennes (MSBP). De plus, nous démontrons l'utilisation de QSBP avec un modèle basé sur l'action ; cela offre des avantages supplémentaires en termes de gestion de l'auto-occlusion et de réduction supplémentaire de l'espace de recherche. Nous présentons une analyse qualitative et quantitative de l’approche proposée avec des résultats encourageants.
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Kittiya KHONGKRAPHAN, Pakorn KAEWTRAKULPONG, "Efficient Human Body Tracking by Quick Shift Belief Propagation" in IEICE TRANSACTIONS on Information,
vol. E94-D, no. 4, pp. 905-912, April 2011, doi: 10.1587/transinf.E94.D.905.
Abstract: We propose a novel and efficient approach for tracking 2D articulated human body parts. In our approach, the human body is modeled by a graphical model where each part is represented by a node and the relationship between a pair of adjacent parts is indicated by an edge in the graph. Various approaches have been proposed to solve such problems, but efficiency is still a vital problem. We present a new Quick Shift Belief Propagation (QSBP) based approach which benefits from Quick Shift, a simple and efficient mode seeking method, in a part based belief propagation model. The unique aspect of this model is its ability to efficiently discover modes of the underlying marginal probability distribution while preserving the accuracy. This gives QSBP a significant advantage over approaches like Belief Propagation (BP) and Mean Shift Belief Propagation (MSBP). Moreover, we demonstrate the use of QSBP with an action based model; this provides additional advantages of handling self-occlusion and further reducing the search space. We present qualitative and quantitative analysis of the proposed approach with encouraging results.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E94.D.905/_p
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@ARTICLE{e94-d_4_905,
author={Kittiya KHONGKRAPHAN, Pakorn KAEWTRAKULPONG, },
journal={IEICE TRANSACTIONS on Information},
title={Efficient Human Body Tracking by Quick Shift Belief Propagation},
year={2011},
volume={E94-D},
number={4},
pages={905-912},
abstract={We propose a novel and efficient approach for tracking 2D articulated human body parts. In our approach, the human body is modeled by a graphical model where each part is represented by a node and the relationship between a pair of adjacent parts is indicated by an edge in the graph. Various approaches have been proposed to solve such problems, but efficiency is still a vital problem. We present a new Quick Shift Belief Propagation (QSBP) based approach which benefits from Quick Shift, a simple and efficient mode seeking method, in a part based belief propagation model. The unique aspect of this model is its ability to efficiently discover modes of the underlying marginal probability distribution while preserving the accuracy. This gives QSBP a significant advantage over approaches like Belief Propagation (BP) and Mean Shift Belief Propagation (MSBP). Moreover, we demonstrate the use of QSBP with an action based model; this provides additional advantages of handling self-occlusion and further reducing the search space. We present qualitative and quantitative analysis of the proposed approach with encouraging results.},
keywords={},
doi={10.1587/transinf.E94.D.905},
ISSN={1745-1361},
month={April},}
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TY - JOUR
TI - Efficient Human Body Tracking by Quick Shift Belief Propagation
T2 - IEICE TRANSACTIONS on Information
SP - 905
EP - 912
AU - Kittiya KHONGKRAPHAN
AU - Pakorn KAEWTRAKULPONG
PY - 2011
DO - 10.1587/transinf.E94.D.905
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E94-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2011
AB - We propose a novel and efficient approach for tracking 2D articulated human body parts. In our approach, the human body is modeled by a graphical model where each part is represented by a node and the relationship between a pair of adjacent parts is indicated by an edge in the graph. Various approaches have been proposed to solve such problems, but efficiency is still a vital problem. We present a new Quick Shift Belief Propagation (QSBP) based approach which benefits from Quick Shift, a simple and efficient mode seeking method, in a part based belief propagation model. The unique aspect of this model is its ability to efficiently discover modes of the underlying marginal probability distribution while preserving the accuracy. This gives QSBP a significant advantage over approaches like Belief Propagation (BP) and Mean Shift Belief Propagation (MSBP). Moreover, we demonstrate the use of QSBP with an action based model; this provides additional advantages of handling self-occlusion and further reducing the search space. We present qualitative and quantitative analysis of the proposed approach with encouraging results.
ER -