based on AdaBoost

YANG Ying1，LIU Wei-guo2，ZHONG Ling1，LI Ya-wen1

（1. School of Mechanical & automation，Northeastern University，Shenyang 110819，China.

2. Zhejiang Key Laboratory of Automobile Safety Technology，Hangzhou 311228，China）

Abstract：Aiming at the pedestrian detection and identification for vehicle aided safety driving system，a research was conducted which is focus on the problems of real-time and veracity affected by illumination for pedestrian detection algorithmic. The on line updating pedestrian detection classifiers technology was used to detect and recognize the pedestrian which are in front of the vehicles. An improved AdaBoost pedestrian detection optimum algorithmic was presented. According to positive and negative samples' error rate while training

pedestrian detection classifiers，the weight of error recognizing rate was on line updated. It could reduce the classifier's series and the calculation complexity，further more，guarantee the overall detection rates. The ability to adapting the environment was improved by adopting extended like-Haar characters to reduce the arithmetic sensitivity. The experimental results show that the improved AdaBoost arithmetic need less detecting time and higher robust than traditional method. This arithmetic can satisfy the request of detecting pedestrians appeared ahead of the vehicles.

Key words：pedestrian detection；Adaboost arithmetic；classifier