Research Article

Article:Region of Interest Tracking In Video Sequences

by  T.Johncy Rani, S.Suja Priyadharsini
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 3 - Issue 7
Published: June 2010
Authors: T.Johncy Rani, S.Suja Priyadharsini
10.5120/740-1046
PDF

T.Johncy Rani, S.Suja Priyadharsini . Article:Region of Interest Tracking In Video Sequences. International Journal of Computer Applications. 3, 7 (June 2010), 32-36. DOI=10.5120/740-1046

                        @article{ 10.5120/740-1046,
                        author  = { T.Johncy Rani,S.Suja Priyadharsini },
                        title   = { Article:Region of Interest Tracking In Video Sequences },
                        journal = { International Journal of Computer Applications },
                        year    = { 2010 },
                        volume  = { 3 },
                        number  = { 7 },
                        pages   = { 32-36 },
                        doi     = { 10.5120/740-1046 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2010
                        %A T.Johncy Rani
                        %A S.Suja Priyadharsini
                        %T Article:Region of Interest Tracking In Video Sequences%T 
                        %J International Journal of Computer Applications
                        %V 3
                        %N 7
                        %P 32-36
                        %R 10.5120/740-1046
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

Tracking a region-of-interest (ROI) in a video is still a challenging task. Various high level applications rely on tracking. e.g, motion picture indexing, object recognition, video surveillance, audiovisual postproduction etc. Initially ROI is defined in a reference frame and the purpose is to determine the ROI in subsequent target frames in video sequences. The region was detected by determining the similarity measures between the reference and the target frames. Similarity measures between the frames are determined using two classical methods like sum of squared differences(SSD) and sum of absolute differences(SAD). This paper deals with the method of ROI tracking in video sequences by estimating the colour and geometric features between the frames and the similarity measures was determined using the Kullback- Leibler Divergence. The increase of description features improves the accuracy. Their combination leads to high dimensional PDFs. Tracking experiments were performed on several standard video sequences and its efficiency was proved.

References
Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Region-of-interest(ROI) Similarity Measures Colour and geometric features Probability density function Kullback-Leibler divergence

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