Abstract:In the current era, the majority of public places such as supermarket, public garden, malls, university campus, etc. are under video surveillance. There is a need to provide essential security and monitor unusual anomaly activities at such places. The major drawback in the traditional approach, that there is a need to perform manual operation for 24 ? 7 and also there are possibilities of human errors. This paper focuses on anomaly detection and activity recognition of humans in the videos. Computer vision ha… Show more
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