IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
An Efficient Human Action Recognition System Using Single Camera and Feature Points
K.MAITHILI, K.RAJESWARI, R.MOHANAPRIYA, D.KRITHIKA Assistant Professor, Department of Information Technology, Christ College of Eng. and Technology, Puducherry, India B.Tech, Final Year, Department of Information Technology, Christ College of Eng. and Technology, Puducherry, India
Abstract: In this paper, an efficient human action recognition system using feature points , single camera method and based on neural network representation recognition is proposed. By now, indicating action videos is based on learning rarely related human body posture method called Self Organizing Maps (SOM). From human body posture by Fuzzy distances, prototypes will represent time in -variant action representation. An many number of cameras can be used in order to recognize actions using a Bayesian framework. The algorithm is used to train data from a multi-camera setup. Due to the growing interest in visual surveillance has led to human action recognition. So we propose a new and efficient method for human action recognition system using single camera and feature points. Our proposed method overcomes the problems in the existing system and recognizes the action of the required human. The system is developed in such a way, first it is trained using the feature extraction and feature tree method and then system will be capable of identifying the action from postures. We prove that our proposed is very efficient and can recognize actions quickly too.
Keywords: Human action recognition, multilayer perceptrons, feature tree, visual surveillance.
How to Cite:
[1] K.MAITHILI, K.RAJESWARI, R.MOHANAPRIYA, D.KRITHIKA Assistant Professor, Department of Information Technology, Christ College of Eng. and Technology, Puducherry, India B.Tech, Final Year, Department of Information Technology, Christ College of Eng. and Technology, Puducherry, India , βAn Efficient Human Action Recognition System Using Single Camera and Feature Points,β International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE)
This work is licensed under a Creative Commons Attribution 4.0 International License.