Author : Chidanand.H 1
Date of Publication :17th April 2018
Abstract: This paper proposes a real time human daily activity recognition using a single stationary camera. The system can recognize activities such as raising or waving hand(s), jumping and walking. Actions are described by a feature vector comprising both trajectory information and a set of local motion descriptors. Feature extraction is done using LBP TOP method. Action recognition is achieved via probabilistic search of image feature databases representing previously seen actions. For activity detection and tracking, we use motion detection algorithms such as frame differencing and feature correlation and finally classification is by kNN classifier. Activity recognition can be exploited to great social benefits, especially in real-life, human centric applications such as elder care and healthcare. Recognizing complex activities remains a challenging and active area of research and the nature of human activities poses different challenges.
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