Co-occurrence-based Adaptive Background Model for Robust Object Detection

被引：0
|
作者：
Liang, Dong [1 ]
Kaneko, Shun'ichi [1 ]
Hashimoto, Manabu [2 ]
Iwatao, Kenji [3 ]
Zhao, Xinyue [4 ]
Satoh, Yutaka [3 ]
机构：
[1] Hokkaido Univ, Sapporo, Hokkaido 060, Japan
[2] Chukyo Univ, Aichi, Japan
[3] AIST, Tokyo, Japan
[4] Zhejiang Univ, Hangzhou 310027, Peoples R China
来源：
2013 10TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE (AVSS 2013) | 2013年
关键词：
REAL-TIME TRACKING;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
An illumination-invariant background model for detecting objects in dynamic scenes is proposed. It is robust in the cases of sudden illumination fluctuation as well as burst moving background. Unlike previous works, it distinguishes objects from a dynamic background using co-occurrence character between a target pixel and its supporting pixels in the form of multiple pixel pairs. Experiments used several challenging datasets that proved the robust performance of object detection in various environments.
引用
收藏
页码：401 / 406
页数：6
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