From bikers to surfers: Visual recognition of Urban tribes

Publikation: Konferencebidrag › Paper › Forskning › fagfællebedømt

Standard

From bikers to surfers : Visual recognition of Urban tribes. / Kwak, Iljung S.; Murillo, Ana C.; Belhumeur, Peter N.; Kriegman, David; Belongie, Serge.

2013. Paper præsenteret ved 2013 24th British Machine Vision Conference, BMVC 2013, Bristol, Storbritannien.

Publikation: Konferencebidrag › Paper › Forskning › fagfællebedømt

Harvard

Kwak, IS, Murillo, AC, Belhumeur, PN, Kriegman, D & Belongie, S 2013, 'From bikers to surfers: Visual recognition of Urban tribes', Paper fremlagt ved 2013 24th British Machine Vision Conference, BMVC 2013, Bristol, Storbritannien, 09/09/2013 - 13/09/2013. https://doi.org/10.5244/C.27.14

APA

Kwak, I. S., Murillo, A. C., Belhumeur, P. N., Kriegman, D., & Belongie, S. (2013). From bikers to surfers: Visual recognition of Urban tribes. Paper præsenteret ved 2013 24th British Machine Vision Conference, BMVC 2013, Bristol, Storbritannien. https://doi.org/10.5244/C.27.14

Vancouver

Kwak IS, Murillo AC, Belhumeur PN, Kriegman D, Belongie S. From bikers to surfers: Visual recognition of Urban tribes. 2013. Paper præsenteret ved 2013 24th British Machine Vision Conference, BMVC 2013, Bristol, Storbritannien. https://doi.org/10.5244/C.27.14

Author

Kwak, Iljung S. ; Murillo, Ana C. ; Belhumeur, Peter N. ; Kriegman, David ; Belongie, Serge. / From bikers to surfers : Visual recognition of Urban tribes. Paper præsenteret ved 2013 24th British Machine Vision Conference, BMVC 2013, Bristol, Storbritannien.

Bibtex

@conference{b98d0f599d3d486faedd55081be404a9,
title = "From bikers to surfers: Visual recognition of Urban tribes",
abstract = "The terms Biker, Punk, Hipster, Goth or Surfer often spark visual depictions of individuals with very distinct fashion styles. These visually salient styles can provide insight into the social identity of an individual. However, despite its potential usefulness, little work has been done to automatically classify images of people into social categories. We tackle this problem by analyzing pictures of groups of individuals and creating models to represent them. We capture the features that distinguish each subculture and show promising results for automatic classification. This work gives vision algorithms access to the social identity of an individual and helps improve the quality of socially motivated image search, relevance of advertisements, and recommendations of social groups.",
author = "Kwak, {Iljung S.} and Murillo, {Ana C.} and Belhumeur, {Peter N.} and David Kriegman and Serge Belongie",
year = "2013",
doi = "10.5244/C.27.14",
language = "English",
note = "2013 24th British Machine Vision Conference, BMVC 2013 ; Conference date: 09-09-2013 Through 13-09-2013",

}

RIS

TY - CONF

T1 - From bikers to surfers

T2 - 2013 24th British Machine Vision Conference, BMVC 2013

AU - Kwak, Iljung S.

AU - Murillo, Ana C.

AU - Belhumeur, Peter N.

AU - Kriegman, David

AU - Belongie, Serge

PY - 2013

Y1 - 2013

N2 - The terms Biker, Punk, Hipster, Goth or Surfer often spark visual depictions of individuals with very distinct fashion styles. These visually salient styles can provide insight into the social identity of an individual. However, despite its potential usefulness, little work has been done to automatically classify images of people into social categories. We tackle this problem by analyzing pictures of groups of individuals and creating models to represent them. We capture the features that distinguish each subculture and show promising results for automatic classification. This work gives vision algorithms access to the social identity of an individual and helps improve the quality of socially motivated image search, relevance of advertisements, and recommendations of social groups.

AB - The terms Biker, Punk, Hipster, Goth or Surfer often spark visual depictions of individuals with very distinct fashion styles. These visually salient styles can provide insight into the social identity of an individual. However, despite its potential usefulness, little work has been done to automatically classify images of people into social categories. We tackle this problem by analyzing pictures of groups of individuals and creating models to represent them. We capture the features that distinguish each subculture and show promising results for automatic classification. This work gives vision algorithms access to the social identity of an individual and helps improve the quality of socially motivated image search, relevance of advertisements, and recommendations of social groups.

UR - http://www.scopus.com/inward/record.url?scp=84898408833&partnerID=8YFLogxK

U2 - 10.5244/C.27.14

DO - 10.5244/C.27.14

M3 - Paper

AN - SCOPUS:84898408833

Y2 - 9 September 2013 through 13 September 2013

ER -

ID: 302046576