NDLI: Revisiting pose estimation with foreshortening compensation and color information

Content Provider	IEEE Xplore Digital Library
Author	Setia, Achint Katti, Anoop R. Mittal, Anurag
Copyright Year	2014
Description	Author affiliation: Department of Computer Science & Engineering, Indian Institute of Technology Madras, Chennai, India (Setia, Achint; Katti, Anoop R.; Mittal, Anurag)
Abstract	This paper addresses the problem of upper body pose estimation. The task is to detect and estimate 2D human configuration in static images for six parts: head, torso, and left-right upper and lower arms. The common approach to solve this has been the Pictorial Structure method (Felzenszwalb and Huttenlocher, 2005). We present this as a graphical model inference problem and use the loopy belief propagation algorithm for inference. When a human appears in fronto-parallel plane, fixed size part detectors are sufficient and give reliable detection. But when parts like lower and upper arms move out of the plane, we observe foreshortening and the part detectors become erroneous. We propose an approach that compensates foreshortening in the upper and lower arms, and effectively prunes the search state space of each part. Additionally, we introduce two extra pairwise constraints to exploit the color similarity information between parts during inference to get better localization of the upper and lower arms. Finally, we present experiments and results on two challenging datasets (Buffy and ETHZ Pascal), showing improvements on the lower arms accuracy and comparable results for other parts.
Starting Page	31
Ending Page	38
File Size	2638028
Page Count	8
File Format	PDF
ISBN	9789897581335
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-05
Publisher Place	Portugal
Access Restriction	Subscribed
Rights Holder	SCITEPRESS
Subject Keyword	Torso Head Image color analysis Part Based Model Detectors Kinematics Foreshortening Compensation Upper Body Pose Estimation Color Similarity Loopy Belief Propagation Standards
Content Type	Text
Resource Type	Article

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