Transitions of the Multi-Scale Singularity Trees

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

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Transitions of the Multi-Scale Singularity Trees. / Somchaipeng, Kerawit; Sporring, Jon; Kreiborg, Sven; Johansen, Peter.

Deep Structure, Singularities, and Computer Vision. <Forlag uden navn>, 2005. p. 223-233 (Lecture notes in computer science, Vol. 3753/2005).

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

Harvard

Somchaipeng, K, Sporring, J, Kreiborg, S & Johansen, P 2005, Transitions of the Multi-Scale Singularity Trees. in Deep Structure, Singularities, and Computer Vision. <Forlag uden navn>, Lecture notes in computer science, vol. 3753/2005, pp. 223-233, First International Workshop in Deep Structure, Singularities, and Computer Vision (DSSCV), Maastricht, Netherlands, 29/11/2010. https://doi.org/10.1007/11577812_20

APA

Somchaipeng, K., Sporring, J., Kreiborg, S., & Johansen, P. (2005). Transitions of the Multi-Scale Singularity Trees. In Deep Structure, Singularities, and Computer Vision (pp. 223-233). <Forlag uden navn>. Lecture notes in computer science Vol. 3753/2005 https://doi.org/10.1007/11577812_20

Vancouver

Somchaipeng K, Sporring J, Kreiborg S, Johansen P. Transitions of the Multi-Scale Singularity Trees. In Deep Structure, Singularities, and Computer Vision. <Forlag uden navn>. 2005. p. 223-233. (Lecture notes in computer science, Vol. 3753/2005). https://doi.org/10.1007/11577812_20

Author

Somchaipeng, Kerawit ; Sporring, Jon ; Kreiborg, Sven ; Johansen, Peter. / Transitions of the Multi-Scale Singularity Trees. Deep Structure, Singularities, and Computer Vision. <Forlag uden navn>, 2005. pp. 223-233 (Lecture notes in computer science, Vol. 3753/2005).

Bibtex

@inproceedings{fdd2cff0524711dd8d9f000ea68e967b,
title = "Transitions of the Multi-Scale Singularity Trees",
abstract = "Multi-Scale Singularity Trees(MSSTs) [10] are multi-scale image descriptors aimed at representing the deep structures of images. Changes in images are directly translated to changes in the deep structures; therefore transitions in MSSTs. Because MSSTs can be used to represent the deep structure of images efficiently, it is important to investigate and understand their transitions and impacts. We present four kinds of MSST transitions and discuss the potential advantages of Saddle-Based MSSTs over Extrema-Based MSSTs. The study of MSST transitions presented in this paper is an important step towards the development of the image matching and indexing algorithms based on MSSTs.",
author = "Kerawit Somchaipeng and Jon Sporring and Sven Kreiborg and Peter Johansen",
year = "2005",
doi = "10.1007/11577812_20",
language = "English",
isbn = "978-3-540-29836-6",
series = "Lecture notes in computer science",
publisher = "<Forlag uden navn>",
pages = "223--233",
booktitle = "Deep Structure, Singularities, and Computer Vision",
note = "null ; Conference date: 29-11-2010",

}

RIS

TY - GEN

T1 - Transitions of the Multi-Scale Singularity Trees

AU - Somchaipeng, Kerawit

AU - Sporring, Jon

AU - Kreiborg, Sven

AU - Johansen, Peter

N1 - Conference code: 1

PY - 2005

Y1 - 2005

N2 - Multi-Scale Singularity Trees(MSSTs) [10] are multi-scale image descriptors aimed at representing the deep structures of images. Changes in images are directly translated to changes in the deep structures; therefore transitions in MSSTs. Because MSSTs can be used to represent the deep structure of images efficiently, it is important to investigate and understand their transitions and impacts. We present four kinds of MSST transitions and discuss the potential advantages of Saddle-Based MSSTs over Extrema-Based MSSTs. The study of MSST transitions presented in this paper is an important step towards the development of the image matching and indexing algorithms based on MSSTs.

AB - Multi-Scale Singularity Trees(MSSTs) [10] are multi-scale image descriptors aimed at representing the deep structures of images. Changes in images are directly translated to changes in the deep structures; therefore transitions in MSSTs. Because MSSTs can be used to represent the deep structure of images efficiently, it is important to investigate and understand their transitions and impacts. We present four kinds of MSST transitions and discuss the potential advantages of Saddle-Based MSSTs over Extrema-Based MSSTs. The study of MSST transitions presented in this paper is an important step towards the development of the image matching and indexing algorithms based on MSSTs.

U2 - 10.1007/11577812_20

DO - 10.1007/11577812_20

M3 - Article in proceedings

SN - 978-3-540-29836-6

T3 - Lecture notes in computer science

SP - 223

EP - 233

BT - Deep Structure, Singularities, and Computer Vision

PB - <Forlag uden navn>

Y2 - 29 November 2010

ER -

ID: 5015450