A method to detect victims in search and rescue operations using template matching

We present an approach to vision-based person detection in robotic applications that uses template matching. We detect people using templates of the human silhouette. In our approach, we detect borders on each image, then apply a distance transform, and then match templates at different scales. Our system integrates silhouette, corners (point of interest) and skin presence in order to obtain more robust results in the detection of victims in search and rescue operations. Further, we describe the automatic generation of templates from a set of photographs of the object of interest.