Deep Learning Approaches for Human Activity Recognition in Video Surveillance - A Survey

Abstract

Recognition of the human activities in videos has gathered numerous demands in various applications of computer vision such as Ambient Assisted Living, intelligent surveillance, Human Computer interaction. One of the most pioneering technique for Human Activity Recognition is based upon deep learning and this paper focuses on various approaches based on that. Convolution Neural Network and Recurrent Neural Networks are mostly used in deep learning architectures. Deep Learning have the capacity of automatic learning of the features from the input modality. Analysis based on Methodology, Accuracy, classifier and datasets is presented in this survey paper.