Auto-scaled incremental tensor subspace learning for region based rate control application

Peng Zhang; Sabu Emmanuel; Yanning Zhang; Xuan Jing

doi:10.1007/978-3-642-12297-2_52

Auto-scaled incremental tensor subspace learning for region based rate control application

Peng Zhang, Sabu Emmanuel, Yanning Zhang, Xuan Jing

School of Computer Science

Nanyang Technological University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, we proposed a method that employs the auto-scaled incremental eigenspace learning to locate the salient distortion areas continually in the video to serve the purpose of region based rate control application. Compared to other locating methods, the auto-scaled incremental eigenspace learning locating method can achieve locating the salient distortion areas robustly and accurately, and specifically in real-time. In addition, for the case that there exists the overlap/occlusion between different salient distortion areas, the proposed method can also obtain accurate location information which could make the region based rate control and bit allocation to reach higher efficiency in many applications. The experiment results of the proposed algorithm demonstrate the subject visual quality of the video has been improved greatly.

Original language	English
Title of host publication	Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers
Pages	538-547
Number of pages	10
Edition	PART 3
DOIs	https://doi.org/10.1007/978-3-642-12297-2_52
State	Published - 2010
Event	9th Asian Conference on Computer Vision, ACCV 2009 - Xi'an, China Duration: 23 Sep 2009 → 27 Sep 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 3
Volume	5996 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	9th Asian Conference on Computer Vision, ACCV 2009
Country/Territory	China
City	Xi'an
Period	23/09/09 → 27/09/09

Keywords

Incremental tensor subspace
Region based
Tracking

Access to Document

10.1007/978-3-642-12297-2_52

Cite this

Zhang, P., Emmanuel, S., Zhang, Y., & Jing, X. (2010). Auto-scaled incremental tensor subspace learning for region based rate control application. In Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers (PART 3 ed., pp. 538-547). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5996 LNCS, No. PART 3). https://doi.org/10.1007/978-3-642-12297-2_52

Zhang, Peng ; Emmanuel, Sabu ; Zhang, Yanning et al. / Auto-scaled incremental tensor subspace learning for region based rate control application. Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers. PART 3. ed. 2010. pp. 538-547 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).

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title = "Auto-scaled incremental tensor subspace learning for region based rate control application",

abstract = "In this paper, we proposed a method that employs the auto-scaled incremental eigenspace learning to locate the salient distortion areas continually in the video to serve the purpose of region based rate control application. Compared to other locating methods, the auto-scaled incremental eigenspace learning locating method can achieve locating the salient distortion areas robustly and accurately, and specifically in real-time. In addition, for the case that there exists the overlap/occlusion between different salient distortion areas, the proposed method can also obtain accurate location information which could make the region based rate control and bit allocation to reach higher efficiency in many applications. The experiment results of the proposed algorithm demonstrate the subject visual quality of the video has been improved greatly.",

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Zhang, P, Emmanuel, S, Zhang, Y & Jing, X 2010, Auto-scaled incremental tensor subspace learning for region based rate control application. in Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers. PART 3 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 5996 LNCS, pp. 538-547, 9th Asian Conference on Computer Vision, ACCV 2009, Xi'an, China, 23/09/09. https://doi.org/10.1007/978-3-642-12297-2_52

Auto-scaled incremental tensor subspace learning for region based rate control application. / Zhang, Peng; Emmanuel, Sabu; Zhang, Yanning et al.
Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers. PART 3. ed. 2010. p. 538-547 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5996 LNCS, No. PART 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - In this paper, we proposed a method that employs the auto-scaled incremental eigenspace learning to locate the salient distortion areas continually in the video to serve the purpose of region based rate control application. Compared to other locating methods, the auto-scaled incremental eigenspace learning locating method can achieve locating the salient distortion areas robustly and accurately, and specifically in real-time. In addition, for the case that there exists the overlap/occlusion between different salient distortion areas, the proposed method can also obtain accurate location information which could make the region based rate control and bit allocation to reach higher efficiency in many applications. The experiment results of the proposed algorithm demonstrate the subject visual quality of the video has been improved greatly.

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Zhang P, Emmanuel S, Zhang Y, Jing X. Auto-scaled incremental tensor subspace learning for region based rate control application. In Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers. PART 3 ed. 2010. p. 538-547. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3). doi: 10.1007/978-3-642-12297-2_52

Auto-scaled incremental tensor subspace learning for region based rate control application

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