Unusual Event Detection from Surveillance

Tamilmani, G.; Uma, S.; Sivakumari, S.

doi:10.1007/978-981-19-3015-7_35

Cited by 1 publication

(1 citation statement)

References 7 publications

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“…This is even though, in nature, normal vehicle recognition and odd occurrences might be highly distinct. The detection, localization, and categorization of various objects in images have each been the subject of several strategies presented in the research literature (Tamilmani et al 2022). The issue with automated LPR (ALPR) is that it recognizes the number of a vehicle's number plate based on photographs of the plate.…”

Section: Related Workmentioning

confidence: 99%

Smart evaluation of videos for unusual-event identification in automated vehicle monitoring systems

Yadav,

Sharma,

Ojha

2023

Multidiscip. Sci. J.

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Many methods have been tried to perfect vehicle recognition, which includes quickly locating the same objects in cameras with different sensor types and perhaps propagating trustworthy information across cameras to improve detection. In this study, we look at various important issues and provide a new method for spotting certain abnormalities. We suggest an automated vehicle monitoring system (AVMS) to enhance detection accuracy. If the current reading from a certain local monitor is out of the ordinary, that monitor will issue a notification, and all of those alerts will go toward deciding whether or not an abnormal event has occurred. The effective implementation of any large-scale surveillance system relies on our algorithm meeting several parameters. It simply takes a few minutes to set up and is completely hands-free. The experimental findings demonstrate the effectiveness and simplicity of the suggested approach, with the assembled image quality being on the level with that of state-of-the-art techniques.

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Section: Related Workmentioning

confidence: 99%