VRank: Voting system on Ranking model for human age estimation

Tekoing Lim, Kai Lung Hua, Hong Cyuan Wang, Kai Wen Zhao, Min Chun Hu, Wen-Huang Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Ranking algorithms have proven the potential for human age estimation. Currently, a common paradigm is to compare the input face with reference faces of known age to generate a ranking relation whereby the first-rank reference is exploited for labeling the input face. In this paper, we proposed a framework to improve upon the typical ranking model, called Voting system on Ranking model (VRank), by leveraging relational information (comparative relations, i.e. if the input face is younger or older than each of the references) to make a more robust estimation. Our approach has several advantages: firstly, comparative relations can be explicitly involved to benefit the estimation task; secondly, few incorrect comparisons will not influence much the accuracy of the result, making this approach more robust than the conventional approach; finally, we propose to incorporate the deep learning architecture for training, which extracts robust facial features for increasing the effectiveness of classification. In comparison to the best results from the state-of-the-art methods, the VRank showed a significant outperformance on all the benchmarks, with a relative improvement of 5.74% ∼ 69.45% (FG-NET), 19.09% ∼ 68.71% (MORPH), and 0.55% ∼ 17.73% (IoG).

Original languageEnglish
Title of host publication2015 IEEE 17th International Workshop on Multimedia Signal Processing, MMSP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467374781
DOIs
StatePublished - 30 Nov 2015
Event17th IEEE International Workshop on Multimedia Signal Processing, MMSP 2015 - Xiamen, China
Duration: 19 Oct 201521 Oct 2015

Publication series

Name2015 IEEE 17th International Workshop on Multimedia Signal Processing, MMSP 2015

Conference

Conference17th IEEE International Workshop on Multimedia Signal Processing, MMSP 2015
CountryChina
CityXiamen
Period19/10/1521/10/15

Keywords

  • Bismuth
  • Estimation
  • Face
  • Feature extraction
  • Machine learning
  • Robustness
  • Support vector machines

Fingerprint Dive into the research topics of 'VRank: Voting system on Ranking model for human age estimation'. Together they form a unique fingerprint.

Cite this