Face detection for low power event detection in intelligent surveillance system
Hyung-Il Kim, Seung Ho Lee, Jung Ik Moon, Hyun-Sang Park, Yong Man Ro · 2014
Recently, the development of intelligent surveillance system increasingly requires low power consumption. For the power saving, this paper presents an event detection function based on automatically detected human faces, which adaptively convert from low power camera mode to high performance camera mode. We propose an efficient face detection (FD) method for operating under the low power camera mode. By employing two-stage structure (i.e., region-of-interest (ROI) selection and false positive (FP) reduction), the proposed FD method requires a very low computational complexity and memory requirements without sacrificing the face detection robustness. Experimental results demonstrated that the proposed FD could be implemented in low power video cameras with promising performance.