Hardware feasibility analysis for motion segmentation initialization

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Standard

Hardware feasibility analysis for motion segmentation initialization. / Tripathi, Subarna; Youngbae Hwang, Y.; Sung-Joon, Jang; Belongie, Serge; Truong, Nguyen.

I: ISOCC 2014 - International SoC Design Conference, 16.04.2015, s. 148-149.

Publikation: Bidrag til tidsskrift › Konferenceartikel › Forskning › fagfællebedømt

Harvard

Tripathi, S, Youngbae Hwang, Y, Sung-Joon, J, Belongie, S & Truong, N 2015, 'Hardware feasibility analysis for motion segmentation initialization', ISOCC 2014 - International SoC Design Conference, s. 148-149. https://doi.org/10.1109/ISOCC.2014.7087670

APA

Tripathi, S., Youngbae Hwang, Y., Sung-Joon, J., Belongie, S., & Truong, N. (2015). Hardware feasibility analysis for motion segmentation initialization. ISOCC 2014 - International SoC Design Conference, 148-149. https://doi.org/10.1109/ISOCC.2014.7087670

Vancouver

Tripathi S, Youngbae Hwang Y, Sung-Joon J, Belongie S, Truong N. Hardware feasibility analysis for motion segmentation initialization. ISOCC 2014 - International SoC Design Conference. 2015 apr. 16;148-149. https://doi.org/10.1109/ISOCC.2014.7087670

Author

Tripathi, Subarna ; Youngbae Hwang, Y. ; Sung-Joon, Jang ; Belongie, Serge ; Truong, Nguyen. / Hardware feasibility analysis for motion segmentation initialization. I: ISOCC 2014 - International SoC Design Conference. 2015 ; s. 148-149.

Bibtex

@inproceedings{6a13467401d34922b59423effa01cd8b,
title = "Hardware feasibility analysis for motion segmentation initialization",
abstract = "We analyze and evaluate different initialization methods for motion layers segmentation, a powerful mid-level vision tool. We estimate 6-D affine motion models from the optical flow corresponding to different over-segmentations. Over-segmentations can be either uniform rectangular blocks; or adaptive sized rectangular blocks; or super-pixels; or based on any other clustering methods. We present performance analysis of motion segmentation initialization algorithms on video sequences and discuss the relative pros and cons of these methods in terms of hardware implementation issues.",
keywords = "affine motion, layered representation, optical flow, superpixel, video segmentation",
author = "Subarna Tripathi and {Youngbae Hwang}, Y. and Jang Sung-Joon and Serge Belongie and Nguyen Truong",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 11th International SoC Design Conference, ISOCC 2014 ; Conference date: 03-11-2014 Through 06-11-2014",
year = "2015",
month = apr,
day = "16",
doi = "10.1109/ISOCC.2014.7087670",
language = "English",
pages = "148--149",
journal = "ISOCC 2014 - International SoC Design Conference",

}

RIS

TY - GEN

T1 - Hardware feasibility analysis for motion segmentation initialization

AU - Tripathi, Subarna

AU - Youngbae Hwang, Y.

AU - Sung-Joon, Jang

AU - Belongie, Serge

AU - Truong, Nguyen

N1 - Publisher Copyright: © 2014 IEEE.

PY - 2015/4/16

Y1 - 2015/4/16

N2 - We analyze and evaluate different initialization methods for motion layers segmentation, a powerful mid-level vision tool. We estimate 6-D affine motion models from the optical flow corresponding to different over-segmentations. Over-segmentations can be either uniform rectangular blocks; or adaptive sized rectangular blocks; or super-pixels; or based on any other clustering methods. We present performance analysis of motion segmentation initialization algorithms on video sequences and discuss the relative pros and cons of these methods in terms of hardware implementation issues.

AB - We analyze and evaluate different initialization methods for motion layers segmentation, a powerful mid-level vision tool. We estimate 6-D affine motion models from the optical flow corresponding to different over-segmentations. Over-segmentations can be either uniform rectangular blocks; or adaptive sized rectangular blocks; or super-pixels; or based on any other clustering methods. We present performance analysis of motion segmentation initialization algorithms on video sequences and discuss the relative pros and cons of these methods in terms of hardware implementation issues.

KW - affine motion

KW - layered representation

KW - optical flow

KW - superpixel

KW - video segmentation

UR - http://www.scopus.com/inward/record.url?scp=84929428392&partnerID=8YFLogxK

U2 - 10.1109/ISOCC.2014.7087670

DO - 10.1109/ISOCC.2014.7087670

M3 - Conference article

AN - SCOPUS:84929428392

SP - 148

EP - 149

JO - ISOCC 2014 - International SoC Design Conference

JF - ISOCC 2014 - International SoC Design Conference

T2 - 11th International SoC Design Conference, ISOCC 2014

Y2 - 3 November 2014 through 6 November 2014

ER -

ID: 301829472