Open AccessEmbedded Video Surveillance Based Moving Object Detection and Tracking
Author(s) -
Dhaya Chinnathambi*,
Poonkavithai Kalamegam
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b2601.098319
Subject(s) - computer vision , computer science , artificial intelligence , optical flow , video tracking , object detection , feature (linguistics) , tracking (education) , computation , tracking system , foreground detection , object (grammar) , image (mathematics) , pattern recognition (psychology) , kalman filter , psychology , pedagogy , linguistics , philosophy , algorithm
Background reckoning and the foreground, play prominent roles in the tasks of visual detection and tracking of objects. Moving Object Detection has been widely used in sundry discipline such as intelligent systems, security systems, video monitoring systems, banking places, provisionary systems, and so on. In this paper proposes moving objects detection and tracking method based on Embedded Video Surveillance. The method is based on using lines computed by a gradient-based optical flow and an edge detector gradient-based optical flow and edges are well matched for accurate computation of velocity, not much attention is paid to creating systems for tracking objects using this feature. The proposed method is compared with a recent work, proving its superior performance and when we want to represent high quality videos and images with, lower bit rate, and also suitable for real-world live video applications. This method reduces influences of foreground objects to the background model. The simulation results show that the background image can be obtained precisely and the moving objects recognition is achieved effectively