Abnormal Event Detection at 150 FPS in MATLAB

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 r...

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Bibliographic Details
Published in2013 IEEE International Conference on Computer Vision pp. 2720 - 2727
Main Authors Lu, Cewu, Shi, Jianping, Jia, Jiaya
Format Conference Proceeding Journal Article
LanguageEnglish
Published IEEE 01.12.2013
Subjects
abnormal event detection
Computer vision
Conferences
dictionary learning
Learning
Least squares method
MATLAB
Optimization
real-time
Running
Silicon
Small scale
Surveillance
surveillance video
Testing
Training
Training data
Videos
Online AccessGet full text
ISSN1550-5499
DOI10.1109/ICCV.2013.338

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Summary: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 140-150 frames per second on average when computing on an ordinary desktop PC using MATLAB.
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ISSN:1550-5499
DOI:10.1109/ICCV.2013.338