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International Journal of Computer Vision

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01-12-2018

Fast Abnormal Event Detection

Authors: Cewu Lu, Jianping Shi, Weiming Wang, Jiaya Jia

Published in: International Journal of Computer Vision | Issue 8/2019

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Abstract

Fast abnormal event detection meets the growing demand to process an enormous number of surveillance videos. Based on the inherent redundancy of video structures, we propose an efficient sparse combination learning framework with both batch and online solvers. It achieves decent performance in the detection phase without compromising result quality. The extremely fast execution speed is guaranteed owing to the fact that our method effectively turns the original complicated problem into a few small-scale least square optimizations. 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 single core desktop PC using MATLAB.

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Title: Fast Abnormal Event Detection
Authors: Cewu Lu
Jianping Shi
Weiming Wang
Jiaya Jia
Publication date: 01-12-2018
Publisher: Springer US
Published in: International Journal of Computer Vision / Issue 8/2019
Print ISSN: 0920-5691
Electronic ISSN: 1573-1405
DOI: https://doi.org/10.1007/s11263-018-1129-8

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