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@article{164604,
        author = {Siddhant Patil and Rutuj Gedam and Prayojita Urade and Vidish Worah and Dr. Rahila Shaikh},
        title = {Realtime Action Recognition},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {12},
        pages = {1563-1566},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=164604},
        abstract = {Real-time action recognition is the process of automatically identifying and classifying human actions in real-time video streams. This task involves detecting and analyzing human movements and activities, such as standing, sitting, and gestures, in a continuous stream of video frames. The goal of real-time action recognition is to enable machines to understand and interpret human actions as they occur, allowing for applications in various fields such as surveillance, human-computer interaction, sports analysis, and healthcare monitoring. To achieve real-time action recognition, advanced computer vision and machine learning techniques are typically employed. These techniques may include deep learning models, motion analysis algorithms ,feature extraction methods, and temporal modeling approaches. Overall, real-time action recognition plays a crucial role in enabling intelligent systems to interact with and respond to human actions in real-world environments},
        keywords = {Deep Learning, Computer Vision, Action Recognition},
        month = {},
        }