Human Activity Recognition and Prediction
نویسندگان
چکیده
Human activity recognition (HAR) has become one of the most active research topics in image processing and pattern recognition [1]. Detecting specific activities in a live feed or searching in video archives still relies almost completely on human resources. Detecting multiple activities in real-time video feeds is currently performed by assigning multiple analysts to simultaneously watch the same video stream. Manual analysis of video is labor intensive, fatiguing, and error prone. Solving the problem of recognizing human activities from video can lead to improvements in several applications fields like in surveillance systems, human computer interfaces, sports video analysis, digital shopping assistants, video retrieval, gaming and health-care [30, 25, 12, 15].
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تاریخ انتشار 2015