NDLI: Mean-shift tracker with face-adjusted model

Content Provider	IEEE Xplore Digital Library
Author	Choe, J.G. Joon-Hong Seok Ju-Jang Lee
Copyright Year	2008
Description	Author affiliation: Electr. Eng. & Comput. Sci., Korea Adv. Inst. of Sci. & Technol., Daejeon (Joon-Hong Seok; Ju-Jang Lee) \|\| Robot. Program, Korea Adv. Inst. of Sci. & Technol., Daejeon (Choe, J.G.)
Abstract	Mean-shift algorithm shows robust performances in various object-tracking technologies including face tracking. Due to its robustness and accuracy, mean-shift algorithm is regarded as one of the best ways to apply in object-tracking technology in computer vision fields. However, it has a drawback of getting into a bottleneck state when faced with a speedy object moving beyond its window size within one image frame interval time. The time required to calculate mean-shift vector could be much lessened with lesser memory when color model is adjusted to the previously known target information. This paper shows the building process of target-adjusted model with a non-uniform quantization. The target color model dealt in this paper is the one used for deriving mean-shift vector. It is a kernel model containing both the color and distance information. This paper gives scheme to efficiently deal with color information in the model. Through a proper selection of color bins, unimportant color values were reduced to a small amount. As a result, the computing time of the mean-shift vector in face-tracking was shortened while maintaining robustness and accuracy.
Starting Page	816
Ending Page	819
File Size	455499
Page Count	4
File Format	PDF
ISBN	9788995003893
DOI	10.1109/ICCAS.2008.4694610
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-14
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	ICROS
Subject Keyword	Target tracking Face recognition Quantization Electronic mail Face detection Face tracking Robotics and automation Face-adjusted Model LUT(Look Up Table) Focusing Mean-shift algorithm Robustness Kernel Pixel
Content Type	Text
Resource Type	Article

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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
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