Exploring Prior Knowledge for Pedestrian Detection

In this paper, we aim to explore the role of prior knowledge for pedestrian detection. The main idea is to integrate human body priors into the design of features. To this end, we propose the symmetric features and cross-channel features so as to capture the specific information of human body. Experimental results demonstrate that our detector achieves state-of-the-art performance. What’s more, the evaluation results on "scale" subsets of Caltech-USA show that our detector performs best at medium scale and therefore has great potential to be integrated into real-world applications.