Malatesh S.H, Gayathri .V


Object tracking is the process of locating moving objects over time using camera. It has wide number of applications like security and surveillance, traffic control, video editing, medical imaging etc. It can be a time consuming process due to the large amount of data contained in video. The objective of tracking is to associate target objects in consecutive video frames. To initiate object tracking an algorithm analyzes video frames and outputs the movement of targets between the frames. There are a number of algorithms each having its own strengths and weakness. Considering the intended use is important when choosing the algorithm. Our aim in the Video Analytics (VA) project is to address obstacles in both image-retrieval and research that uses extreme-scale archives of video data that employs a human-machine hybrid process for analyzing moving images.

This paper proposes kalman filter based methods for object tracking, addressing two major issues such as places more interpretive power in the hands of the human user through novel visualizations of video data and uses a customized on-demand configuration that enables iterative queries. The purpose of this project was to demonstrate how a real time system for image registration and moving object detection can be used to track objects over frames of video.This project uses Open CV (Open Computer Vision) routines and visual c++ to implement the object tracking.

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