Featureless small object detection and tracking
无表观特征小目标检测与跟踪

The detection and tracking of small and/or indistinct objects is a challenge in computer vision, since it is difficult for current detection and tracking algorithms to extract appropriate apparent features from small and/or indistinct objects. We found by observing video data that the small moving objects can be distinguished from noisy background due to their regular motion pattern. Based on this finding, we proposed a novel method for solving the challenging problem of small and/or indistinct object detection and tracking. The contribution of this paper is the denoising algorithm for small object segmentation and the dynamic programming algorithm for route optimization in tracking. Extensive experiments show the promising results in both accuracy and robustness of the proposed method.