Background-Subtraction in Thermal Imagery Using Contour Saliency

We present a new contour-based background-subtraction technique to extract foreground objects in widely varying thermal imagery. Statistical background-subtraction is first used to identify local regions-of-interest. Within each region, input and background gradient information are combined to form a Contour Saliency Map. After thinning, 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 for several difficult thermal sequences and compared to alternate approaches. We quantify the results using manually segmented thermal imagery to demonstrate the robustness of the approach.