Dynamic Active Search for quick object detection with pan-tilt-zoom camera

This paper proposes a search method for detecting known objects quickly in 3D environments with a pan-tilt-zoom camera. In our previous work, we proposed an algorithm named Active Search that greatly reduces the number of calculations required to obtain a match between a reference object and an input image using color histograms. Here, we describe two improvements we have made to Active Search for such practical applications as robots and surveillance. First, we increased the robustness as regards the color histogram changes that result from different lighting conditions and camera angles by using multiple reference images and a pixel color vector quantization. Second, we reduced the number of camera operations (pan, tilt and zoom) by using a best-direction-first and upper bound pruning strategies. We call this camera control Dynamic Active Search. Experiments show an improvement in object detection accuracy and a 78% reduction in detection time.