Rosepreet Kaur Bhogal1,*, V. Devendran2
Computer Systems Science and Engineering, Vol.47, No.3, pp. 2759-2772, 2023, DOI:10.32604/csse.2023.034862
Abstract Human activity recognition is a recent area of research for researchers. Activity recognition has many applications in smart homes to observe and track toddlers or oldsters for their safety, monitor indoor and outdoor activities, develop Tele immersion systems, or detect abnormal activity recognition. Three dimensions (3D) skeleton data is robust and somehow view-invariant. Due to this, it is one of the popular choices for human action recognition. This paper proposed using a transversal tree from 3D skeleton data to represent videos in a sequence. Further proposed two neural networks: convolutional neural network recurrent neural network_1 (CNN_RNN_1), used to find the… More >
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