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Performance Evaluation of Object Tracking Technique Based on Position Vectors

V Purandhar Reddy, K Thirumala Reddy, Y.B.Dawood, K.M.YaagnaTheja, C.Munesh, M.V.L.Sraavani

Pages - 124 - 131 | Revised - 05-04-2013 | Published - 30-04-2013

Published in International Journal of Image Processing (IJIP)

Volume - 7 Issue - 2 | Publication Date - April 2013 Table of Contents

MORE INFORMATION

References | Cited By (1) | Abstracting & Indexing

KEYWORDS

Object Tracking, DWT, DTCWT, Feature Vector, Block Matching

ABSTRACT

In this paper, a novel algorithm for moving object tracking based on position vectors has proposed. The position vector of an object in first frame of a video has been extracted based on selection of region of interest. Based on position vector in first frame object direction has shown in nine different directions. We extract nine position vectors for nine different directions. With these position vectors next frame is cropped into nine blocks. We exploit block matching of the first frame with nine blocks of the next frame in a simple feature space by Descrete wavelet transform and dual tree complex wavelet transform. The matched block is considered as tracked object and its position vector is a reference location for the next successive frame. We describe performance evaluation and algorithm in detail to perform simulation experiments of object tracking using different feature vectors which verifies the tracking algorithm efficiency.

CITED BY (1)

1	Jatoth, R. K., Gopisetty, S., & Hussain, M. (2015). Performance Analysis of Alpha Beta Filter, Kalman Filter and Meanshift for Object Tracking in Video Sequences. International Journal of Image, Graphics and Signal Processing (IJIGSP), 7(3), 24.

ABSTRACTING & INDEXING

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