基于Codebook背景建模的视频行人检测

针对视频序列,Codebook背景建模算法能检测出其中的运动物体,但却无法识别行人.而大部分基于支持向量机(SVM)训练的行人分类器,需要通过滑动窗口遍历图像检测行人.为加快行人检测的速度,提出将传统的行人分类器融入到Codebook背景建模算法中,通过背景建模算法为行人检测提供候选区域,减少搜索范围,降低了行人误检率;并根据行人的特点,构建临时块模型定期将满足条件的前景区域更新到背景模型中,解决了Codebook背景建模算法不能应对光照突变的问题.实验结果表明:所提算法能应对光照突变所带来的干扰,实现视频行人实时检测.

Pedestrian detection based on Codebook background modeling in video

As for video sequences,Codebook background modeling algorithm can detect moving objects,but cannot recognize pedestrians. Meanwhile,most pedestrians classifiers are based on support vector machine(SVM) training has to traverse through the whole image,by sliding window to detect pedestrians. To speed up pedestrian detection process,algorithm of traditional pedestrian classification device fused in Codebook background modeling algorithm is proposed provide candidate regionals by background modeling algorithm for pedestrian detection reduce the search range and error rate of the pedestrian. According to features of pedestrians,temporary block model is built to regularly update into background model,which solve the problem that Codebook background modeling algorithm cannot suit the illumination abrupt variation. Experimental results demonstrate that the proposed algorithm can deal with the interference caused by sudden light variation,it can achieve the real-time pedestrian detection in video.