基于Adaboost与背景差分级联的室内人数统计方法

A People Counting Method Based on Adaboost and Background Subtraction in Indoor Environment

针对室内监控视频环境,提出了一种基于Adaboost与背景差分级联的室内人数统计方法.算法采用Harr-Like局部特征用于人员特征检测,使用Adaboost分类器进行训练,最后的检测结果采用级联背景差分修复算法减少误报与漏报数目.实验证明,能较准确地完成自习室中人数的统计,且具有较好的鲁棒性.

A novel people counting method based on Adaboost and background subtraction algorithm is presented for indoor video surveillance. Firstly,the local features of Haar-Like,Adaboost algorithm are adopted to produce the strong classifier for human body detection. Then the cascade method based on the results of detection and background Subtraction algorithm is proposed to reduce the number of false positives and false negatives samples. Finally,the experiment results show that the proposed method can accurately complete the number of statistics in the classroom with good robustness.