NDLI: Human pose estimation with global motion cues

Content Provider	IEEE Xplore Digital Library
Author	Qingxuan Shi Huijun Di Yao Lu Feng Lv
Copyright Year	2015
Description	Author affiliation: Beijing Lab. of Intell. Inf. Technol., Beijing Inst. of Technol., Beijing, China (Qingxuan Shi; Huijun Di; Yao Lu; Feng Lv)
Abstract	We present a novel method to estimate full-body human pose in video sequence by incorporating global motion cues. It has been demonstrated that temporal constraints can largely enhance the pose estimation. Most current approaches typically employ local motion to propagate pose detections to supplement the pose candidates. However, the local motion estimation is often inaccurate under fast movements of body parts and unhelpful when no strong detections achieved in adjacent frames. In this paper, we propose to propagate the detection in each frame using the global motion estimation. Benefiting from the strong detections, our algorithm first produces reasonable trajectory hypotheses for each body part. Then, we cast pose estimation as an optimization problem defined on these trajectories with spatial links between body parts. In the optimization process, we select body part trajectory rather than body part candidate to infer the human pose. Experimental results demonstrate significant performance improvement in comparison with the state-of-the-art methods.
Starting Page	442
Ending Page	446
File Size	1734431
Page Count	5
File Format	PDF
e-ISBN	9781479983391
DOI	10.1109/ICIP.2015.7350837
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-27
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Trajectory Motion estimation Video sequences Tracking Biological system modeling Detectors global motion estimation Pose estimation pose detection
Content Type	Text
Resource Type	Article

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