Proceedings of the First International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India

Research Article

Multi-View Feature Clustering Technique for Detection and Classification of Human Actions

  • @INPROCEEDINGS{10.4108/eai.16-5-2020.2304034,
        author={Syed  Ahmed and Nirmala S Guptha and Afifa Salsabil Fathima and S  Ashwini},
        title={Multi-View Feature Clustering Technique for Detection and Classification of Human Actions},
        proceedings={Proceedings of the First  International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India},
        publisher={EAI},
        proceedings_a={ICASISET},
        year={2021},
        month={1},
        keywords={human action detection pattern recognition clustering classification},
        doi={10.4108/eai.16-5-2020.2304034}
    }
    
  • Syed Ahmed
    Nirmala S Guptha
    Afifa Salsabil Fathima
    S Ashwini
    Year: 2021
    Multi-View Feature Clustering Technique for Detection and Classification of Human Actions
    ICASISET
    EAI
    DOI: 10.4108/eai.16-5-2020.2304034
Syed Ahmed1,*, Nirmala S Guptha2, Afifa Salsabil Fathima3, S Ashwini3
  • 1: Dr. T. Thimmaiah Institute of Technology, KGF, India
  • 2: Sri Venkateshwara College of Engineering, Bengaluru, India
  • 3: Cambridge Institute of Technology, Bengaluru, India
*Contact email: syed@drttit.edu.in

Abstract

Recognizing the actions performed by any person is the most suc-cessful applications in pattern recognition. Detecting the action in a moving camera influences dynamic view changes, is based on spatio-temporal infor-mation at multiple temporal scales. In this paper, we are presenting a system that is dependent on actions based on multi-view information. These multi-view features are extracted from various temporal scales. The GMM and Prewitt edge filter is used for detecting background and foreground image. The Nearest Mean Classifier is used to cluster features vector’s of moving object. The experiment results demonstrated using Kth dataset producing 98% of accuracy.