Deep Learning Approaches for Human Action Recognition in Video Data

arXiv:2403.06810v1 Announce Type: new
Abstract: Human action recognition in videos is a critical task with significant implications for numerous applications, including surveillance, sports analytics, and healthcare. The challenge lies in creating models that are both precise in their recognition capabilities and efficient enough for practical use. This study conducts an in-depth analysis of various deep learning models to address this challenge. Utilizing a subset of the UCF101 Videos dataset, we focus on Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), …

abstract action recognition analytics applications arxiv capabilities challenge cs.cv data deep learning healthcare human lies practical recognition sports study surveillance type video video data videos