Deformable Multi-object Tracking Using Full Pixel Matching of Image

Hisato Aota, Kazuhiro Ota, Yuichi Yaguchi, Ryuichi Oka

Abstract: We propose a novel method for the segmentation of deformable objects and the extraction of motion features for tracking objects in video data. The method adopts an algorithm called two-dimensional continuous dynamic programming (2DCDP) for extracting pixel-wise trajectories. A clustering algorithm is applied to a set of pixel trajectories to determine a shape of deformable objects each of which corresponds to a trajectory cluster. We conduct experiments to compare our method with conventional methods such as KLT tracker and SIFT. The experiment shows that our method is more powerful than the conventional methods.