Cewu Lu Jianping Shi Jiaya Jia
The Chinese Univeristy of Hong Kong
Speedy abnormal event detection meets the growing demand to process an enormous number of surveillance videos. Based on inherent redundancy of video structures, we propose an efficient sparse combination learning framework. It achieves decent performance in the detection phase without compromising result quality. The short running time is guaranteed because the new method effectively turns the original complicated problem to one in which only a few costless small-scale least square optimization steps are involved. Our method reaches high detection rates on benchmark datasets at a speed of 1000 ~ 1200 frames per second on average when computing on an ordinary desktop PC using MATLAB.
|CPU (Single Core)||Memory||Platform|
"Abnormal Event Detection at 150 FPS in MATLAB"
Cewu Lu, Jianping Shi, Jiaya Jia
IEEE International Conference on Computer Vision (ICCV), 2013
[Code] (upon request to Dr. Lu <email@example.com>)