Open AccessIntelligent Video Surveillance using Deep Learning
Author(s) -
Vijay Bhanudas Gujar,
Arbaaz Shaikh,
A. B. Bagwan,
Pooja Dixit,
Nidhi Todkar
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.c5233.029320
Subject(s) - computer science , object detection , artificial intelligence , focus (optics) , deep learning , object (grammar) , process (computing) , identification (biology) , big data , computer vision , computer security , machine learning , pattern recognition (psychology) , data mining , physics , botany , optics , biology , operating system
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.