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@article{144359,
        author = {S.Nhivethasre and M.Ramya},
        title = {Automatic Abnormal Activity Detection for Road Accidents using Video Surveillance Systems for Intelligent Transportation Systems},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {3},
        number = {10},
        pages = {213-217},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=144359},
        abstract = {The road accidents in modern urban areas are increased to uncertain level and it is must to avoid the loss of human life due to accident. Traffic accidents are one of the leading causes of fatalities. Nowadays, numerous surveillance applications use multiple types of data and features benefiting from their uncorrelated contributions. Hence, the analysis, standardization and fusion of complex content, especially visual, have become a fundamental problem to enhance surveillance systems by increasing their accuracy, robustness and reliability. But it requires manual checking to detect for any abnormal activity which requires human intervention. Hence traffic accident detection system for automatically detecting, recording, and reporting traffic accidents is proposed.},
        keywords = {traffic accidents, surveillance, and automatic abnormal activity detection},
        month = {},
        }