Pedestrian detection based on modeling computation of visual attention
Liu Qion · Journal of Beijing Information Science & Technology University · 2014
A pedestrian detection method is proposed based on the modeling computation of visual attention. First,a saliency map is generated through multi-scale center-surround computation and normalization,based on extraction of saliency feature of pedestrian object. Meanwhile,a skin color feature map is computed based on the skin color Gaussian model to express the unique character of pedestrian object. A guided map is achieved through refining the skin color features by implementing accumulation of specific pixel for every block and threshold average filtering. Moreover,the objective area prediction is completed by offset weighted of saliency map and guided map. Experimental results on Penn-Fudan pedestrian database and real videos show that the proposed computational model outperforms other existing models in terms of detection precision. Compared with traditional object detection method, the proposed method can save time drastically and improve detection efficiency.