Abstract
We present a new contour analysis technique to detect people in thermal imagery. Background-subtraction is first used to identify local regions-of-interest. Gradient information within each region is then combined into a contour saliency map. To extract contour fragments, a watershed-based selection algorithm is used. A path-constrained A* search is employed to complete any broken contours, from which silhouettes are formed. Results using thermal video sequences demonstrate the capability of the approach to robustly detect people across a wider range of environmental conditions than is possible with standard approaches.
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