ONLINE VISUAL OBJECT TRACKING USING INCREMENTAL DISCRIMINATIVE COLOR LEARNING

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

ASVADI ALIREZA; MAHDAVINATAJ HAMI; KARAMI MOHAMMAD REZA; BALEGHI YASSAR

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: The CSI Journal on Computer Science and Engineering Year:2014 | Volume:12 | Issue:2-4 (B) Page(s): 16-28

Download Full-Text

View:

410

Download:

164

Cites:

Information Journal Paper

Title

ONLINE VISUAL OBJECT TRACKING USING INCREMENTAL DISCRIMINATIVE COLOR LEARNING

Author(s)

ASVADI ALIREZA | MAHDAVINATAJ HAMI | KARAMI MOHAMMAD REZA | BALEGHI YASSAR | Issue Writer Certificate

Keywords

VISUAL OBJECT TRACKING

3D JOINT RGB HISTOGRAM

LOG-LIKELIHOOD RATIO

INCREMENTAL LEARNING

MEAN-SHIFT LOCALIZATION

Abstract

This paper presents a method for tracking an object in a sequence of images given its location in the first frame. Recently, a class of techniques called discriminative methods has shown promising results. These methods are based on training a classifier to distinguish the object from surrounding background. However, discriminative methods do not explicitly model the object. Therefore, noisy samples are likely to interfere and cause visual drift. In this paper, 3D JOINT RGB HISTOGRAMs of the object and surrounding background are used to develop an object model. An incremental color learning scheme with a forgetting factor is applied to evolve the object model during tracking. It is shown the proposed method can handle visual drift effectively. Evaluated against five state of the art methods, experiments demonstrate superior results of the proposed tracking algorithm. Implemented in MATLAB, the algorithm runs at 17.2 frames per second, including image input/output time.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

APA: Copy

ASVADI, ALIREZA, MAHDAVINATAJ, HAMI, KARAMI, MOHAMMAD REZA, & BALEGHI, YASSAR. (2014). ONLINE VISUAL OBJECT TRACKING USING INCREMENTAL DISCRIMINATIVE COLOR LEARNING. THE CSI JOURNAL ON COMPUTER SCIENCE AND ENGINEERING, 12(2-4 (B)), 16-28. SID. https://sid.ir/paper/688801/en

Vancouver: Copy

ASVADI ALIREZA, MAHDAVINATAJ HAMI, KARAMI MOHAMMAD REZA, BALEGHI YASSAR. ONLINE VISUAL OBJECT TRACKING USING INCREMENTAL DISCRIMINATIVE COLOR LEARNING. THE CSI JOURNAL ON COMPUTER SCIENCE AND ENGINEERING[Internet]. 2014;12(2-4 (B)):16-28. Available from: https://sid.ir/paper/688801/en

IEEE: Copy

ALIREZA ASVADI, HAMI MAHDAVINATAJ, MOHAMMAD REZA KARAMI, and YASSAR BALEGHI, “ONLINE VISUAL OBJECT TRACKING USING INCREMENTAL DISCRIMINATIVE COLOR LEARNING,” THE CSI JOURNAL ON COMPUTER SCIENCE AND ENGINEERING, vol. 12, no. 2-4 (B), pp. 16–28, 2014, [Online]. Available: https://sid.ir/paper/688801/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops