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Human Action Recognition and Prediction: A Survey

Kong, Yu ; Fu, Yun

International journal of computer vision, 2022-05, Vol.130 (5), p.1366-1401 [Periódico revisado por pares]

New York: Springer US

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Título:
Human Action Recognition and Prediction: A Survey
Autor: Kong, Yu ; Fu, Yun
Assuntos: Algorithms ; Artificial Intelligence ; Computer Imaging ; Computer Science ; Computer vision ; Datasets ; Human activity recognition ; Human acts ; Human behavior ; Human motion ; Image Processing and Computer Vision ; Machine learning ; Machine vision ; Pattern Recognition ; Pattern Recognition and Graphics ; Predictions ; Surveillance ; Surveys ; Vision ; Vision systems
É parte de: International journal of computer vision, 2022-05, Vol.130 (5), p.1366-1401
Descrição: Derived from rapid advances in computer vision and machine learning, video analysis tasks have been moving from inferring the present state to predicting the future state. Vision-based action recognition and prediction from videos are such tasks, where action recognition is to infer human actions (present state) based upon complete action executions, and action prediction to predict human actions (future state) based upon incomplete action executions. These two tasks have become particularly prevalent topics recently because of their explosively emerging real-world applications, such as visual surveillance, autonomous driving vehicle, entertainment, and video retrieval, etc. Many attempts have been devoted in the last a few decades in order to build a robust and effective framework for action recognition and prediction. In this paper, we survey the complete state-of-the-art techniques in action recognition and prediction. Existing models, popular algorithms, technical difficulties, popular action databases, evaluation protocols, and promising future directions are also provided with systematic discussions.
Editor: New York: Springer US
Idioma: Inglês

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Human Action Recognition and Prediction: A Survey

Kong, Yu ; Fu, Yun

New York: Springer US

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