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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44054

Title: Occluded Human Body Segmentation and its Application to Behavior Analysis
Authors: Jun-Wei Hsieh
Sin-Yu Chen
Chi-Hung Chuang
Miao-Fen Chueh
Shiaw-Shian Yu
Contributors: 國立臺灣海洋大學:資訊工程學系
NTOU:Department of Computer Science and Engineering
Keywords: Humans
Hidden Markov models
Information analysis
Marine technology
Computer industry
Application software
Maintenance engineering
Date: 2010-05
Issue Date: 2017-11-13T07:44:05Z
Publisher: 2010 IEEE International Symposium on Circuits and Systems
Abstract: Abstract:This paper addresses the problem of occluded human segmentation and then uses its results for human behavior recognition. To tackle this ill-posed problem, a novel clustering scheme is proposed for constructing a model space for posture classification. Then, a model-driven approach is proposed for separating an occluded region to individual objects. For reducing the model space, a particle filtering technique is then used for locating possible positions of each occluded object. Then, from the positions, the best model of each occluded object can be then selected using its distance maps. Then, a novel template re-projection technique is proposed for repairing an occluded object to a complete one. Due to occlusions, there will be many posture symbol converting errors in this representation. Instead of using a specific symbol, we code a posture using not only its best matched key posture but also its similarities among other key postures. With the matrix representation, different actions can be more robustly and effectively matched by comparing their KL distance.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44054
Appears in Collections:[資訊工程學系] 演講及研討會

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