A computational approach to finding facial patterns of a babyface

Zi Yi Ke, Mei Chen Yeh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Facial babyishness has a strong impact on social perceptions and interactions; however, the components constituting a babyface remain unclear. In this paper, we present a computational approach for identifying important but less apparent facial patterns of a babyface, using voluminous face images on the web. The proposed approach is built upon computationally efficient data mining techniques. A new image set with ground truth data collected from users and an evaluation approach based on age estimation are presented in the experiment. The results show that the mined patterns are effective for understanding and determining babyfaces. The findings of this study should provide information for future investigations on the prediction and analysis of trait impressions using the patterns.

Original languageEnglish
Title of host publicationICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval
PublisherAssociation for Computing Machinery, Inc
Pages235-238
Number of pages4
ISBN (Electronic)9781450343596
DOIs
Publication statusPublished - 2016 Jun 6
Event6th ACM International Conference on Multimedia Retrieval, ICMR 2016 - New York, United States
Duration: 2016 Jun 62016 Jun 9

Publication series

NameICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval

Other

Other6th ACM International Conference on Multimedia Retrieval, ICMR 2016
CountryUnited States
CityNew York
Period16/6/616/6/9

Fingerprint

Data mining
Experiments

Keywords

  • Babyface recognition
  • Facial landmark
  • Visual mining

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction
  • Software

Cite this

Ke, Z. Y., & Yeh, M. C. (2016). A computational approach to finding facial patterns of a babyface. In ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval (pp. 235-238). (ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval). Association for Computing Machinery, Inc. https://doi.org/10.1145/2911996.2912042

A computational approach to finding facial patterns of a babyface. / Ke, Zi Yi; Yeh, Mei Chen.

ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval. Association for Computing Machinery, Inc, 2016. p. 235-238 (ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ke, ZY & Yeh, MC 2016, A computational approach to finding facial patterns of a babyface. in ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval. ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval, Association for Computing Machinery, Inc, pp. 235-238, 6th ACM International Conference on Multimedia Retrieval, ICMR 2016, New York, United States, 16/6/6. https://doi.org/10.1145/2911996.2912042
Ke ZY, Yeh MC. A computational approach to finding facial patterns of a babyface. In ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval. Association for Computing Machinery, Inc. 2016. p. 235-238. (ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval). https://doi.org/10.1145/2911996.2912042
Ke, Zi Yi ; Yeh, Mei Chen. / A computational approach to finding facial patterns of a babyface. ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval. Association for Computing Machinery, Inc, 2016. pp. 235-238 (ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval).
@inproceedings{155108f6a97747ac8558ea43e96044af,
title = "A computational approach to finding facial patterns of a babyface",
abstract = "Facial babyishness has a strong impact on social perceptions and interactions; however, the components constituting a babyface remain unclear. In this paper, we present a computational approach for identifying important but less apparent facial patterns of a babyface, using voluminous face images on the web. The proposed approach is built upon computationally efficient data mining techniques. A new image set with ground truth data collected from users and an evaluation approach based on age estimation are presented in the experiment. The results show that the mined patterns are effective for understanding and determining babyfaces. The findings of this study should provide information for future investigations on the prediction and analysis of trait impressions using the patterns.",
keywords = "Babyface recognition, Facial landmark, Visual mining",
author = "Ke, {Zi Yi} and Yeh, {Mei Chen}",
year = "2016",
month = "6",
day = "6",
doi = "10.1145/2911996.2912042",
language = "English",
series = "ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval",
publisher = "Association for Computing Machinery, Inc",
pages = "235--238",
booktitle = "ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval",

}

TY - GEN

T1 - A computational approach to finding facial patterns of a babyface

AU - Ke, Zi Yi

AU - Yeh, Mei Chen

PY - 2016/6/6

Y1 - 2016/6/6

N2 - Facial babyishness has a strong impact on social perceptions and interactions; however, the components constituting a babyface remain unclear. In this paper, we present a computational approach for identifying important but less apparent facial patterns of a babyface, using voluminous face images on the web. The proposed approach is built upon computationally efficient data mining techniques. A new image set with ground truth data collected from users and an evaluation approach based on age estimation are presented in the experiment. The results show that the mined patterns are effective for understanding and determining babyfaces. The findings of this study should provide information for future investigations on the prediction and analysis of trait impressions using the patterns.

AB - Facial babyishness has a strong impact on social perceptions and interactions; however, the components constituting a babyface remain unclear. In this paper, we present a computational approach for identifying important but less apparent facial patterns of a babyface, using voluminous face images on the web. The proposed approach is built upon computationally efficient data mining techniques. A new image set with ground truth data collected from users and an evaluation approach based on age estimation are presented in the experiment. The results show that the mined patterns are effective for understanding and determining babyfaces. The findings of this study should provide information for future investigations on the prediction and analysis of trait impressions using the patterns.

KW - Babyface recognition

KW - Facial landmark

KW - Visual mining

UR - http://www.scopus.com/inward/record.url?scp=84978696293&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84978696293&partnerID=8YFLogxK

U2 - 10.1145/2911996.2912042

DO - 10.1145/2911996.2912042

M3 - Conference contribution

AN - SCOPUS:84978696293

T3 - ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval

SP - 235

EP - 238

BT - ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval

PB - Association for Computing Machinery, Inc

ER -