A computational approach to finding facial patterns of a babyface

Zi Yi Ke, Mei Chen Yeh

研究成果: 書貢獻/報告類型會議貢獻

摘要

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.

原文英語
主出版物標題ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval
發行者Association for Computing Machinery, Inc
頁面235-238
頁數4
ISBN(電子)9781450343596
DOIs
出版狀態已發佈 - 2016 六月 6
事件6th ACM International Conference on Multimedia Retrieval, ICMR 2016 - New York, 美国
持續時間: 2016 六月 62016 六月 9

出版系列

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

其他

其他6th ACM International Conference on Multimedia Retrieval, ICMR 2016
國家美国
城市New York
期間16/6/616/6/9

指紋

Data mining
Experiments

ASJC Scopus subject areas

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

引用此文

Ke, Z. Y., & Yeh, M. C. (2016). A computational approach to finding facial patterns of a babyface. 於 ICMR 2016 - Proceedings of the 2016 ACM International Conference on Multimedia Retrieval (頁 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).

研究成果: 書貢獻/報告類型會議貢獻

Ke, ZY & Yeh, MC 2016, A computational approach to finding facial patterns of a babyface. 於 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, 頁 235-238, 6th ACM International Conference on Multimedia Retrieval, ICMR 2016, New York, 美国, 16/6/6. https://doi.org/10.1145/2911996.2912042
Ke ZY, Yeh MC. A computational approach to finding facial patterns of a babyface. 於 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. 頁 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 -