Fusion-Based Background-Subtraction using Contour Saliency

Abstract

We present a new contour-based background-subtraction technique using thermal and visible imagery for persistent object detection in urban settings. Statistical backgroundsubtraction in the thermal domain is used to identify the initial regions-of-interest. Color and intensity information are used within these areas to obtain the corresponding regionsof- interest in the visible domain. Within each region, input and background gradient information are combined to form a Contour Saliency Map. The binary contour fragments, obtained from corresponding Contour Saliency Maps, are then combined. An A path-constrained search along watershed boundaries is used to complete and close any broken contour segments. Lastly, the contour image is flood- filled to produce silhouettes. Results of our approach are presented and compared against manually segmented data.