Abstract
Research on automatic human action recognition is gaining more popularity among researchers with the explosion of tremendous amount of video data. The goal of HAR is to deduce one or more people’s actions given a series of observations. There are various applications like surveillance systems, retrieval of video, human and computer interactions, gaming environment, entertainment environment, healthcare system, etc., which require the method of recognizing the human activities in various scenarios. The framework is presented to recognize the actions performed by humans on KTH dataset using spatial–temporal interest points-based detector and the KNN classifier.
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Susmitha, A., Sunanda, Mohanty, M.N., Hota, S. (2023). A Machine Learning Approach for Human Action Recognition. In: Swarnkar, T., Patnaik, S., Mitra, P., Misra, S., Mishra, M. (eds) Ambient Intelligence in Health Care. Smart Innovation, Systems and Technologies, vol 317. Springer, Singapore. https://doi.org/10.1007/978-981-19-6068-0_42
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DOI: https://doi.org/10.1007/978-981-19-6068-0_42
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