Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

In video surveillance the moving object detection and tracking are important research area of computer vision. Tracking moving objects in a real time environment is not easy because of continual deformation of objects during movement. The moving item has many attributes in both temporal and spatial spaces. In the spatial area, objects vary in size while in temporal area they vary in moving speed. To track multiple object in video with optimal window size the Decomposition with Temporal Domain (DTD) is proposed. Thus the moving objects are detected and tracked until it disappears or losses it motion. The proposed strategy can identify and track objects all the while. It reduces the False Alarms Rate (FAR) and increases True Positive Rate (TPR). Moving items with various speeds and sizes are tracked with their optimal window size and the possible shadow is eliminated by the multi frame difference method. The proposed method is compared with Kalman filter and Optical Flow (OF) of Lucas-Kanade method using probabilistic approaches such as FAR and TPR performance is analyzed. Different test results have affirmed the legitimacy and adequacy of the proposed technique. © 2016 IEEE.

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2016 International Conference on Recent Trends in Information Technology, ICRTIT 2016

Efficient detection tracking of multiple moving objects in temporal domain

In computer vision, tracking human pose has received a growing attention in recent years. The existing methods used multi-view videos and camera calibrations to enhance the shape of the object in 3D view. In this paper, tracking and partial reconstruction of the shape of the object from a single view video is identified. The goal of the proposed integrated method is to detect the movement of a person more accurately in 2D view. The integrated method is a combination of Silhouette based pose estimation and Scene flow based pose estimation. The silhouette based pose estimation is used to enhance the shape of the object for 3D reconstruction and scene flow based pose estimation is used to capture the size as well as the stability of the object. By integrating these two poses, the accurate shape of the object has been calculated from a single view video. © 2014 IEEE.