A Survey on Object Detection and Tracking Methods

The goal of object tracking is segmenting a region of interest from a video scene and keeping track of its motion, positioning and occlusion.The object detection and object classification are preceding steps for tracking an object in sequence of images. Object detection is performed to check existence of objects in video and to precisely locate that object. Then detected object can be classified in various categories such as humans, vehicles, birds, floating clouds, swaying tree and other moving objects. Object tracking is performed using monitoring objects’ spatial and temporal changes during a video sequence, including its presence, position, size, shape, etc.Object tracking is used in several applications such as video surveillance, robot vision, traffic monitoring, Video inpainting and Animation. This paper presents a brief survey of different object detection, object classification and object tracking algorithms available in the literature including analysis and comparative study of different techniques used for various stages of tracking.

[1]  Prashant Krishan,et al.  Moving Object Tracking using Gaussian Mixture Model and Optical Flow , 2013 .

[2]  K. Porkumaran,et al.  Improved background subtraction techniques for security in video applications , 2009, 2009 3rd International Conference on Anti-counterfeiting, Security, and Identification in Communication.

[3]  J. Athanesious,et al.  Systematic Survey on Object Tracking Methods in Video , 2012 .

[4]  M. Sankari,et al.  Estimation of Dynamic Background and Object Detection in Noisy Visual Surveillance , 2011 .

[5]  Jae-Yeong Lee,et al.  Visual tracking by partition-based histogram backprojection and maximum support criteria , 2011, 2011 IEEE International Conference on Robotics and Biomimetics.

[6]  A. Vadivel,et al.  Multiple human object tracking using background subtraction and shadow removal techniques , 2010, 2010 International Conference on Signal and Image Processing.

[7]  Darshak G Thakore,et al.  Moving Object Tracking Using Kalman Filter , 2013 .

[8]  A. Rosenfeld,et al.  Background Subtraction Algorithm Based Human Motion Detection , 2013 .

[9]  Chandrika Kamath,et al.  Robust techniques for background subtraction in urban traffic video , 2004, IS&T/SPIE Electronic Imaging.

[10]  Jian Ding,et al.  Object Tracking and Detecting Based on Adaptive Background Subtraction , 2012 .

[11]  Rahul Mishra,et al.  Multiple Object Tracking by Kernel Based Centroid Method for Improve Localization , 2012 .

[12]  J. L. Roux.  An Introduction to the Kalman Filter , 2003 .

[13]  Kai-Wei Lin,et al.  Automatic path modeling by image processing techniques , 2010, 2010 International Conference on Machine Learning and Cybernetics.