Adaptive human silhouette reconstruction based on the exploration of temporal information

Human silhouette reconstruction has a wide range of applications in motion analysis, object segmentation and tracking, etc. In this paper, we propose a human silhouette reconstruction method based on the exploration of temporal information. Given a test silhouette, the proposed method aims to find its reliable templates for reconstruction by using the intrinsic temporal relationship among different frames. To effectively obtain such templates, we propose an adaptive criterion based on the non-negative least square optimization. Experimental results on two challenging datasets demonstrate the effectiveness of our method.