Energy-saving object detection by efficiently rejecting a set of neighboring sub-images

Object detection is crucial for multimedia processing such as image understanding and video analysis. Due to the large amount of images and videos and the limited computational resource, effective and efficient object detection is challenging. Although much effort has been done to develop fast object detection algorithms, little work was concentrated on energy-saving algorithms. Even two detection algorithms that detect objects in the same speed may consume different electronic energies. In this paper, we focus on developing an energy-saving object detection algorithm which can reject a bundle of neighboring sub-images with only one inner-product operation and an acceptable number of addition ones. The total number of multiplications and additions of our algorithm is almost equal to that of the traditional sliding-window method. But in our algorithm the number of multiplication operations is much smaller. Because addition operation consumes less energy than multiplication operation, the proposed method is more energy-saving and efficient. Experimental results on hand detection show that our approach leads to significant improvements in energy and efficiency.

► An energy-saving object detection algorithm is proposed.
► A set of neighboring sub-images can be rejected with as small as one inner-product operation.
► Sub-images that are neighboring in spatial domain are neighboring in feature space in many cases.