Detecting Abnormal Activities using Computer Vision in Big Data Framework
Richa Gupta1, Amit Gupta2, Vikas Tripathi3, Devesh Pratap Singh4, Bhaskar Pant5
1Richa Gupta, Graphic Era Deemed to be University, Dehradun, India.
2Amit Gupta, Graphic Era Hill University, Dehradun, India.
3Dr. Vikas Tripathi, Graphic Era Deemed to be University, Dehradun, India.
4Dr. Devesh Pratap Singh, Graphic Era Deemed to be University, Dehradun, India.
5Dr. Bhaskar Pant, Graphic Era Deemed to be University, Dehradun, India.
Manuscript received on 13 October 2019 | Revised Manuscript received on 20 October 2019 | Manuscript Published on 29 June 2020 | PP: 55-60 | Volume-8 Issue-10S2 August 2019 | Retrieval Number: J101308810S219/2019©BEIESP | DOI: 10.35940/ijitee.J1013.08810S219
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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: The abnormal behaviour of any person can be detected using computer vision. This is an important area in the field of research which is driven by wide variety of domains like intelligent video surveillance. Various techniques can be used in the field of computer vision feature extraction and description scheme. In this paper we have shown the comparison of all the techniques and method used in computer vision for the detection of abnormal activities.
Keywords: Object detection, abnormal activities detection, Event detection, Big data and Computer vision.
Scope of the Article: Social Sciences