Synthesis of Facial Images Based on Relevance Feedback

被引：0

作者：

Xu, Caie ^{[1
]}

Fushimi, Shota ^{[1
]}

Toyoura, Masahiro ^{[1
]}

Xu, Jiayi ^{[2
]}

Li, Honglin ^{[1
]}

Mao, Xiaoyang ^{[1
]}

机构：

[1] Univ Yamanashi, Yamanashi, Japan

[2] Hangzhou Dianzi Univ, Hangzhou, Zhejiang, Peoples R China

来源：

2017 INTERNATIONAL CONFERENCE ON CYBERWORLDS (CW) | 2017年

关键词：

face image synthesis; relevance feedback; optimum-path Forest;

D O I：

10.1109/CW.2017.53

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

We propose a dialogic system based on a relevance feedback strategy that allows for the semiautomatic synthesis of a facial image that only exists in a user's mind. The user is presented with several facial images and judges whether each one resembles the face that he or she is imagining. Based on the feedback from the user, a set of sample facial images are used to train an Optimum-Path Forest classifying the relevance of facial images. An interpolation method is then employed to synthesize new facial images that closely resemble the imagined face. A series of experiments are conducted to evaluate and verify the effectiveness and efficiency of the proposed technique.

引用

页码：210 / 213

页数：4

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