A Super-Fast Online Face Tracking System for Video Surveillance

  • Xiaosong Lan ,
  • Zhiwei Xiong ,
  • Wei Zhang ,
  • Shuxiao li ,
  • Hongxing Chang ,
  • Wenjun Zeng

International Symposium on Circuits and Systems |

Published by IEEE - Institute of Electrical and Electronics Engineers

Publication

In this paper, we propose a novel and practical system for robust online face tracking in surveillance videos. The proposed system has two contributions: 1) sustained high performance for long-term tracking even when faces come in and out of the view frequently, and 2) extremely low complexity which allows for real-time deployment on various platforms. These advantages are achieved by designing a regular update framework based on a state-of-the-art face detector and a new histogram-assisted KLT (HAKLT) tracker. Experimental results demonstrate a superior and super-fast (>100fps) practical face tracking system.