Multiple pedestrian tracking based on multi-layer graph with tracklet segmentation and merging

Abstract

Multiple pedestrian tracking is regarded as a challenging work due to difficulties of occlusion, abrupt motion and changes in appearance. In this paper, we propose a multi-layer graph based data association framework to address occlusion problem. Our framework is hierarchical with three association layers and each layer has its corresponding association method. We generate short tracklets and segment some of them into small pieces based on the segmentation condition in the first layer. The segmented tracklets are merged into long tracklets using spatial-temporal information in the second layer. In the last layer, tracklets in neighboring frame-window are merged to form object track mainly by searching the global maximum overlap ratio of the tracklets. Since appearance information is not available in various scenarios, we don’t use any appearance features in our work. We evaluate our algorithm on extensive sequences including two categories and demonstrate superior experimental results.