@inproceedings{5d318c88d055432c8b8f5f1d01f32f79,
title = "Efficient anomaly detection algorithms for summarizing low quality videos",
abstract = "Many surveillance and security monitoring videos are long and of low quality. Moreover, reviewing and extracting anomaly events in the videos is a lengthy and manually intensive process. In this paper, we present two efficient anomaly detection algorithms based on saliency to detect anomalous events in low quality videos. The events' start times and durations are saved in a video summary for later reviews. The video summary is very short. For example, we have summarized a 14-minute long video into a 16-second video summary. Extensive evaluations of the two algorithms clearly demonstrated the feasibility of these algorithms. A user friendly software tool has also been developed to help human operators review and confirm those events.",
keywords = "Anomaly detection, low quality videos, video summarization",
author = "Chiman Kwan and Jin Zhou and Zheshen Wang and Baoxin Li",
note = "Funding Information: This research was supported by the DARPA under contract # W31P4Q-09-C-0229. The views, opinions and/or findings expressed are those of the author(s) and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government.; Pattern Recognition and Tracking XXIX 2018 ; Conference date: 18-04-2018 Through 19-04-2018",
year = "2018",
doi = "10.1117/12.2303764",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Alam, {Mohammad S.}",
booktitle = "Pattern Recognition and Tracking XXIX",
}