Human Action Recognition using Rule based Fuzzy Motion Feature Templates
Chandra Mani Sharma1, Alaknanda Ashok2, Alok Kumar Singh Kushwaha3
1Chandra Mani Sharma*, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India.
2Alaknanda Ashok, Women Institute of Technology.
3Alok Kumar Singh Kushwaha, Department of CSE, IKGPTU, Jalandhar, India.
Manuscript received on October 12, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 4695-4700 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4855119119/2019©BEIESP | DOI: 10.35940/ijitee.A4855.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper proposes a technique for human activity recognition in a video stream. To achieve high accuracy in activity recognition results, the method in its initial step deploys temporal template matching to recognize activities. As temporal templates are susceptible to get affected by speed, style and performance pattern of activity, so it becomes difficult to accurately differentiate among closely similar activities (e.g walking, running and jogging). The confusion in recognizing activities is reconciled by subsequent rule based activity distinction. The proposed method recognizes the human activities in video on various bench-marked data sets including KTH Dataset and Weizmann Dataset. Experimental results demonstrate the novelty of method with a wide spectrum of varied conditions. The average accuracy of the method is 97.20% under standard conditions.
Keywords: Human Activity Recognition, Computer Vision, Rule Based Approach, Video Content Management and Analysis, Motion Feature Templates
Scope of the Article: Computer Vision