Object Detection Using Adaptive Block-based Background Model

被引：0
|
作者：
Tsai, Wen-Kai
Chen, Jian-Hui
Sheu, Ming-Hwa
Sun, Chi-Chia
机构：
来源：
2016 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS-TAIWAN (ICCE-TW) | 2016年
关键词：
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：
This paper propose an adaptable block-based background modeling and real time image object detection algorithm. In training step, we present adaptable block-based background model that uses major color number to determine the block size. This background model can reduce the memory consumption, efficiently. In detection step, we use one pixel to compare with background model. Then, it can reduce processing time. The experiment results show that we can save 33.9% memory space. Finally, we can achieve 27.25 frames per second for the benchmark video with image size 768X576.
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收藏
页码：45 / 46
页数：2
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