Human Pose Recognition by Combining Static Recognition with Motion Information
Date Issued
2007
Date
2007
Author(s)
Wang, Shao-Ting
DOI
en-US
Abstract
In this thesis, we describe a method which combines static recognition based on single image with motion information to recover human poses from video sequences with two cameras. Silhouettes extracted from two images are used for static recognition. For a pair of observed images, we match the obtained silhouettes with the examples generated from motion capture data using robust shape descriptors to find the solution candidates. In order to solve ambiguity problem which means that different poses may result in the same silhouette and save the computation complexity, the motion information is then introduced to evaluate the motion distance of solution candidates only. We use the intensity change as motion information, and thus error-prediction problem can be successfully overcome. Finally, a weighted-sum method is used for the combination of the results obtained with respect to two cameras. Several video sequences are used to validate the effectiveness of our proposed approach.
Subjects
人體姿態辨識
電腦視覺
虛擬實境
特徵擷取
影像比對
Human pose recognition
Computer vision
Virtual reality
feature extraction
image matching
motion information
Type
thesis
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