ARTICULATED HUMAN POSE TRACKING BASED ON GAME THEORY

被引：0

作者：

Liu, Chenguang ^{[1
]}

Cheng, Hengda ^{[1
]}

Allan, Vicki H. ^{[1
]}

机构：

[1] Utah State Univ, Dept Comp Sci, Logan, UT 84322 USA

来源：

2013 20TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2013) | 2013年

关键词：

Articulated human pose tracking; Game theory; Normal form game; Nash equilibrium;

D O I：

暂无

中图分类号：

TB8 [摄影技术];

学科分类号：

0804 ;

摘要：

Human pose tracking is among the most popular hotspots in the field of computer vision. In this paper, we propose a novel game theory based method for tracking two dimensional articulated human poses in monocular video sequences. A new probability scheme of game theory is introduced into human pose tracking to find optimal solutions of human poses. The possible limb positions are modeled as strategies of agents who play normal form game with adjacent agents. Likelihood measurements and distance constraints are applied to calculate the payoffs of each of the strategies. Finally, the Nash equilibria are found for each normal form game and the human poses are estimated based on them. In the experiments, the effectiveness and efficiency of the proposed algorithm is fully exhibited.

引用

页码：2553 / 2556

页数：4

共 50 条

[41] Human Pose Tracking Based on Both Generic and Specific Appearance Models
Lu, Yao
Li, Ling
Peursum, Patrick
2012 12TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS & VISION (ICARCV), 2012, : 1071 - 1076
[42] Human Pose Tracking algorithm based on Skeleton-Texture model
Yi Ouyang
Zhang, Sanyuan
2009 ETP INTERNATIONAL CONFERENCE ON FUTURE COMPUTER AND COMMUNICATION (FCC 2009), 2009, : 23 - 27
[43] An Ensemble Model using Face and Pose Tracking for Engagement Detection in Game-based Rehabilitation
Lin, Xujie
Cai, Siqi
Chan, Patrick P. K.
Xie, Longhan
2023 2ND ASIA CONFERENCE ON ALGORITHMS, COMPUTING AND MACHINE LEARNING, CACML 2023, 2023, : 445 - 449
[44] Human action recognition in videos with articulated pose information by deep networks
Farrajota, M.
Rodrigues, Joao M. F.
du Buf, J. M. H.
PATTERN ANALYSIS AND APPLICATIONS, 2019, 22 (04) : 1307 - 1318
[45] Estimating articulated human pose from video using shape context
Qiu, XJ
Wang, ZQ
Xia, SH
Li, JT
2005 IEEE INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY (ISSPIT), VOLS 1 AND 2, 2005, : 583 - 588
[46] Human action recognition in videos with articulated pose information by deep networks
M. Farrajota
João M. F. Rodrigues
J. M. H. du Buf
Pattern Analysis and Applications, 2019, 22 : 1307 - 1318
[47] Human Pose Estimation and Tracking via Parsing a Tree Structure Based Human Model
Zhang, Xiaoqin
Li, Changcheng
Hu, Weiming
Tong, Xiaofeng
Maybank, Steve
Zhang, Yimin
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2014, 44 (05): : 580 - 592
[48] A method of hand tracking based on articulated model
Hang, Z
Ruan, QQ
2002 6TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, VOLS I AND II, 2002, : 961 - 964
[49] TRACKING ARTICULATED HUMAN MOVEMENTS WITH A COMPONENT BASED APPROACH TO BOOSTED MULTIPLE INSTANCE LEARNING
Han, Kyuseo
Park, Johnny
Kak, Avinash C.
2013 20TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2013), 2013, : 2460 - 2464
[50] CAPTRA: CAtegory-level Pose Tracking for Rigid and Articulated Objects from Point Clouds
Weng, Yijia
Wang, He
Zhou, Qiang
Qin, Yuzhe
Duan, Yueqi
Fan, Qingnan
Chen, Baoquan
Su, Hao
Guibas, Leonidas J.
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021), 2021, : 13189 - 13198

← 1 2 3 4 5 →