NDLI: Human Pose Regression Through Multiview Visual Fusion

Content Provider	IEEE Xplore Digital Library
Author	Xu Zhao Yun Fu Huazhong Ning Yuncai Liu Huang, T.S.
Copyright Year	1991
Abstract	We consider the problem of estimating 3-D human body pose from visual signals within a discriminative framework. It is challenging because there is a wide gap between complex 3-D human motion and planar visual observation, which makes this a severely ill-conditioned problem. In this paper, we focus on three critical factors to tackle human body pose estimation, namely, feature extraction, learning algorithm, and camera utilization. On the feature level, we describe images using the salient interest points represented by scale-invariant feature transform (SIFT)-like descriptors, in which the position, appearance, and local structural information are encoded simultaneously. On the learning algorithm level, we propose to use Gaussian processes and multiple linear (ML) regression to model the mapping between poses and features. Fusing image information from multiple cameras in different views is of great interest to us on the camera level. We make a comprehensive evaluation on the HumanEva database and get two meaningful insights into the three crucial aspects for human pose estimation: 1) although the choice of feature is very important to the problem, once the learning algorithm becomes efficient, the choice of feature is no longer critical, and 2) the impact of information combination from multiple cameras on pose estimation is closely related to not only the quantity of image information, but also its quality. In most cases, it is true that the more information is involved, the better results can be achieved. But when the information quantity is the same, the differences in quality will lead to totally different performance. Furthermore, dense evaluations demonstrate that our approach is an accurate and robust solution to the human body pose estimation problem.
Sponsorship	IEEE Circuits and Systems Society
Starting Page	957
Ending Page	966
Page Count	10
File Size	1303938
File Format	PDF
ISSN	10518215
Volume Number	20
Issue Number	7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Humans Cameras Robustness Life estimation Feature extraction Gaussian processes Image databases Spatial databases Research and development Image processing multiple views Gaussian processes regression human pose estimation image feature
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Media Technology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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