Visipedia circa 2015

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Visipedia circa 2015. / Belongie, Serge; Perona, Pietro.

In: Pattern Recognition Letters, Vol. 72, 01.03.2016, p. 15-24.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Belongie, S & Perona, P 2016, 'Visipedia circa 2015', Pattern Recognition Letters, vol. 72, pp. 15-24. https://doi.org/10.1016/j.patrec.2015.11.023

APA

Belongie, S., & Perona, P. (2016). Visipedia circa 2015. Pattern Recognition Letters, 72, 15-24. https://doi.org/10.1016/j.patrec.2015.11.023

Vancouver

Belongie S, Perona P. Visipedia circa 2015. Pattern Recognition Letters. 2016 Mar 1;72:15-24. https://doi.org/10.1016/j.patrec.2015.11.023

Author

Belongie, Serge ; Perona, Pietro. / Visipedia circa 2015. In: Pattern Recognition Letters. 2016 ; Vol. 72. pp. 15-24.

Bibtex

@article{b5557150648341e8bc352e12e8372f34,
title = "Visipedia circa 2015",
abstract = "Visipedia is a network of people and machines designed to harvest and organize visual information and make it accessible to anyone who has a visual query. We discuss technical challenges arising from Visipedia and discuss their implications for pattern recognition, computer vision, machine learning and visual psychology. Amongst these are discovering visual information that is implicit in experts' brains and in crowds of people and estimating its accuracy. To motivate our thinking we explore a case study, an automated field guide to the birds of North America. We conclude by discussing research directions that are necessary to make progress on Visipedia. An important realisation is that the study of 'computer vision' and 'machine learning' has to be broadened to include the process of information discovery and the dynamic interaction of people and machines in this context. Human-machine systems with no oracle are now within the scope of pattern recognition, machine learning and computer vision.",
keywords = "Active learning, Computer Vision, Crowdsourcing, Human-machine interaction, Machine learning, Visipedia, Visual psychology, Visual recognition, Wikipedia",
author = "Serge Belongie and Pietro Perona",
note = "Funding Information: We gratefully acknowledge funding from Google, from an ARO/JPL-NASA Stennis Grant NAS7.03001 and the ONR MURI Grant N00014-10-1-0933. Publisher Copyright: {\textcopyright} 2015 Elsevier B.V. All rights reserved.",
year = "2016",
month = mar,
day = "1",
doi = "10.1016/j.patrec.2015.11.023",
language = "English",
volume = "72",
pages = "15--24",
journal = "Pattern Recognition Letters",
issn = "0167-8655",
publisher = "Elsevier BV * North-Holland",

}

RIS

TY - JOUR

T1 - Visipedia circa 2015

AU - Belongie, Serge

AU - Perona, Pietro

N1 - Funding Information: We gratefully acknowledge funding from Google, from an ARO/JPL-NASA Stennis Grant NAS7.03001 and the ONR MURI Grant N00014-10-1-0933. Publisher Copyright: © 2015 Elsevier B.V. All rights reserved.

PY - 2016/3/1

Y1 - 2016/3/1

N2 - Visipedia is a network of people and machines designed to harvest and organize visual information and make it accessible to anyone who has a visual query. We discuss technical challenges arising from Visipedia and discuss their implications for pattern recognition, computer vision, machine learning and visual psychology. Amongst these are discovering visual information that is implicit in experts' brains and in crowds of people and estimating its accuracy. To motivate our thinking we explore a case study, an automated field guide to the birds of North America. We conclude by discussing research directions that are necessary to make progress on Visipedia. An important realisation is that the study of 'computer vision' and 'machine learning' has to be broadened to include the process of information discovery and the dynamic interaction of people and machines in this context. Human-machine systems with no oracle are now within the scope of pattern recognition, machine learning and computer vision.

AB - Visipedia is a network of people and machines designed to harvest and organize visual information and make it accessible to anyone who has a visual query. We discuss technical challenges arising from Visipedia and discuss their implications for pattern recognition, computer vision, machine learning and visual psychology. Amongst these are discovering visual information that is implicit in experts' brains and in crowds of people and estimating its accuracy. To motivate our thinking we explore a case study, an automated field guide to the birds of North America. We conclude by discussing research directions that are necessary to make progress on Visipedia. An important realisation is that the study of 'computer vision' and 'machine learning' has to be broadened to include the process of information discovery and the dynamic interaction of people and machines in this context. Human-machine systems with no oracle are now within the scope of pattern recognition, machine learning and computer vision.

KW - Active learning

KW - Computer Vision

KW - Crowdsourcing

KW - Human-machine interaction

KW - Machine learning

KW - Visipedia

KW - Visual psychology

KW - Visual recognition

KW - Wikipedia

UR - http://www.scopus.com/inward/record.url?scp=84961635328&partnerID=8YFLogxK

U2 - 10.1016/j.patrec.2015.11.023

DO - 10.1016/j.patrec.2015.11.023

M3 - Journal article

AN - SCOPUS:84961635328

VL - 72

SP - 15

EP - 24

JO - Pattern Recognition Letters

JF - Pattern Recognition Letters

SN - 0167-8655

ER -

ID: 301828745