Gait Object Extraction and Recognition in Dynamic and Complex Scene Using Pulse Coupled Neural Network and Feature Fusion

被引：8
|
作者：
Hou, Yimin [1 ,2 ]
Rao, Nini [1 ]
Lun, Xiangmin [2 ]
Liu, Feng [2 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Life Sci & Technol, Chengdu 610054, Peoples R China
[2] Northeast Dianli Univ, Sch Automat Engn, Chuanying 132012, Jilin, Peoples R China
来源：
JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS | 2014年 / 4卷 / 02期
关键词：
Gait Recognition; Dynamic and Complex Scene; Pulse Coupled Neural Network; Feature Fusion; IMAGE; TRANSFORM;
D O I：
10.1166/jmihi.2014.1257
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
This paper proposes a gait object extraction and recognition algorithm in dynamic and complex scene. The improved Pulse Coupled Neural Network (PCNN) is used to extract the gait objects. The initial gait image is employed to train the PCNN and the trained network is used to classify the images followed. After the gait object being extracted and normalized, the gait features, including Gait Energy Image (GEI), Procrustes mean shape, the Fan-Beam transform of GEI and the feature matrix are employed to recognize the gait object. The features above were fused by Euclidean Distance. The image sequences taken from public database and daily life were used in the experiment. The results showed that the method proposed in this paper is effective for dynamic and complex scene.
引用
收藏
页码：325 / 330
页数：6
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