Spatial-Based Joint Component Analysis Using Hybrid Boosting Machine for Detecting Human Carrying Baggage

被引：0
|
作者：
Wahyono [1 ]
Jo, Kang-Hyun [1 ]
机构：
[1] Univ Ulsan, Grad Sch Elect Engn, Ulsan 680749, South Korea
来源：
COMPUTATIONAL COLLECTIVE INTELLIGENCE (ICCCI 2015), PT I | 2015年 / 9329卷
关键词：
Carried baggage detection and classification; Joint component; Video surveillance; HOG; Boosting machine; Mixture model; Support vector machine;
D O I：
10.1007/978-3-319-24069-5_24
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper introduces a new approach for detecting and classifying baggage carried by human in images. The human region is modeled into several components such as head, body, foot and bag. This model uses the location information of baggage relative to human body. Features of each component is extracted. The features are then used to train boosting support vector machine (SVM) and mixture model over component. In experiment, our method achieves promising results in order to build automatic video surveillance system.
引用
收藏
页码：256 / 264
页数：9
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