Intelligent Video Surveillance using Deep Learning
Vijay Bhanudas Gujar1, Arbaaz Shaikh2, Alim Bagwan3, Pooja Dixit4, Nidhi Todkar5
1Mr. Vijay Bhanudas Gujar*, Department of CSE, Dnyanshree Institute of Engineering and Technology, Satara, India.
2Mr. Arbaaz Shaikh, Department of CSE, Dnyanshree Institute of Engineering and Technology, Satara, Maharashtra, India.
3Miss. Pooja Dixit, Department of CSE, Dnyanshree Institute of Engineering and Technology, Satara, Maharashtra, India.
4Mr. Alim Bagwan, Department of CSE, Dnyanshree Institute of Engineering and Technology, Satara, Maharashtra, India.
5Miss. Nidhi Todkar, Department of CSE, Dnyanshree Institute of Engineering and Technology, Satara, Maharashtra, India.
Manuscript received on February 06, 2020. | Revised Manuscript received on February 10, 2020. | Manuscript published on February 30, 2020. | PP: 1314-1317 | Volume-9 Issue-3, February, 2020. | Retrieval Number: C5233029320/2020©BEIESP | DOI: 10.35940/ijeat.C5233.029320
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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: Now days, Big data applications are having most of the importance and space in industry and research area. Surveillance videos are a major contribution to unstructured big data. The main objective of this paper is to give brief about video analysis using deep learning techniques in order to detect suspicious activities. Our main focus is on applications of deep learning techniques in detection the count, no of involved persons and the activity going on in a crowd considering all conditions [9]. This video analysis helps us to achieve security. Security can be defined in different terms like identification of theft, detecting violence etc. Suspicious Human Activity Detection is simply the process of detection of unusual (abnormal)l human activities . For this we need to convert the video into frames and processing these frames helps us to analyze the persons and their activities. There are two modules in this system first one Object Detection Module and Second one is Activity Detection Module .Object detection module detects whether the object is present or not. After detecting the object the next module is going to check whether the activity is suspicious or not. Keywords: Big data, Video surveillance, Deep learning, Crowd analysis, Machine Learning; Violent Activities Detection; Convolutional Neural.
Keywords: Recurrent Neural Network; Long Short-Term Memory