HUANG Cheng-du, HUANG Wen-guang, YAN Bin. Pedestrian detection based on Codebook background modeling in video[J]. 2017, 36(3): 144-146. DOI: 10.13873/J.1000-9787(2017)03-0144-03.
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.