NDLI: Object tracking algorithm based on HSV color histogram and block-sparse representation

Content Provider	IEEE Xplore Digital Library
Author	Chi Xiao Wenjie Chen Huilin Gao
Copyright Year	2015
Description	Author affiliation: Sch. of Autom., Beijing Inst. of Technol., Beijing, China (Chi Xiao; Wenjie Chen; Huilin Gao)
Abstract	Sparse representation has been applied in tracking rapidly. However, most of these methods use the holistic model and grayscale image which result in insensitiveness to color information and ineffectiveness to deformation of non-rigid object. In this paper, we propose a robust and effective tracking method (SRH) based on the block-sparse representation (local information) and HSV color histogram (spatial information). This method not only keeps the merits of block-sparse representation in handling illumination changes and occlusions, but also adds the object color resolution and is not subjected to similar colors interference. It improves the accuracy and efficiency of tracking result. In addition, we calculate the weight of block-sparse representation and HSV color histogram and introduce a fusion method to fuse these two data. Furthermore, the occlusion handling reduces the influence of heavy block, the update strategy guarantees the tracker to adapt to the complex background and morphological changes of target which enhances the reliability of this method. Experimental results compared with several state-of-the-art trackers on challenging sequences demonstrate the robustness and accuracy of the proposed tracking algorithm.
Starting Page	3826
Ending Page	3831
File Size	892229
Page Count	6
File Format	PDF
ISBN	9789881563897
ISSN	19341768
DOI	10.1109/ChiCC.2015.7260229
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Technical Committee on Control Theory, Chinese Association of Automation
Subject Keyword	Histograms Target tracking Dictionaries Image color analysis feature fusion Lighting Fasteners HSV color histogram occlusion handling block-sparse representation
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

MeanShift tracking algorithm with adaptive block color histogram

A target tracking algorithm based on mean shift with feature fusion

Novel block matching algorithm using predictive motion vector for video object tracking based on color histogram

Robust object tracking using color and depth images with a depth based occlusion handling and recovery

Object tracking based on improved MeanShift and SIFT

A particle filter object tracking based on feature and location fusion

Research of kernel particle filtering target tracking algorithm based on multi-feature fusion

Object tracking with occlusion handling using mean shift, Kalman filter and Edge Histogram

Target tracking using color based particle filter

Object tracking algorithm based on HSV color histogram and block-sparse representation

Similar Documents

MeanShift tracking algorithm with adaptive block color histogram

A target tracking algorithm based on mean shift with feature fusion

Novel block matching algorithm using predictive motion vector for video object tracking based on color histogram

Robust object tracking using color and depth images with a depth based occlusion handling and recovery

Object tracking based on improved MeanShift and SIFT

A particle filter object tracking based on feature and location fusion

Research of kernel particle filtering target tracking algorithm based on multi-feature fusion

Object tracking with occlusion handling using mean shift, Kalman filter and Edge Histogram

Target tracking using color based particle filter

Object tracking algorithm based on HSV color histogram and block-sparse representation