Local face sketch synthesis learning

被引：46

作者：

Gao, Xinbo ^{[2
]}

Zhong, Juanjuan ^{[2
]}

Tao, Dacheng ^{[1
]}

Li, Xuelong ^{[3
]}

机构：

[1] Hong Kong Polytech Univ, Biometr Res Ctr, Hong Kong, Hong Kong, Peoples R China

[2] Xidian Univ, Sch Elect Engn, Xian, Shaanxi, Peoples R China

[3] Univ London, Birkbeck Coll, Sch Comp Sci & Informat Syst, London WC1E 7HU, England

来源：

NEUROCOMPUTING | 2008年 / 71卷 / 10-12期

基金：

中国国家自然科学基金;

关键词：

facial sketch synthesis; sketch-photo recognition; E-HMM; selective ensemble; pseudo-sketch;

D O I：

10.1016/j.neucom.2007.10.025

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Facial sketch synthesis (FSS) is crucial in sketch-based face recognition. This paper proposes an automatic FSS algorithm with local strategy based on embedded hidden Markov model (E-HMM) and selective ensemble (SE). By using E-HMM to model the nonlinear relationship between a photo-sketch patch pair, a series of pseudo-sketch patches, generated based on several learned models for a given photo patch, are integrated with SE strategy to synthesize a finer face pseudo-sketch patch. Finally, the intact pseudo-sketch can be generated by combining all synthesized patches. Experimental results illustrate that the proposed FSS algorithm works well. (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：1921 / 1930

页数：10

共 50 条

[1] RESIDUAL LEARNING FOR FACE SKETCH SYNTHESIS
Jiang, Junjun
Yu, Yi
Wang, Zheng
Ma, Jiayi
2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2018, : 1952 - 1956
[2] Face Sketch Synthesis by Multidomain Adversarial Learning
Zhang, Shengchuan
Ji, Rongrong
Hu, Jie
Lu, Xiaoqiang
Li, Xuelong
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 30 (05) : 1419 - 1428
[3] Learning to Deblur Face Images via Sketch Synthesis
Lin, Songnan
Zhang, Jiawei
Pan, Jinshan
Liu, Yicun
Wang, Yongtian
Chen, Jing
Ren, Jimmy
THIRTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THE THIRTY-SECOND INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE AND THE TENTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2020, 34 : 11523 - 11530
[4] Deep Graphical Feature Learning for Face Sketch Synthesis
Zhu, Mingrui
Wang, Nannan
Gao, Xinbo
Li, Jie
PROCEEDINGS OF THE TWENTY-SIXTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2017, : 3574 - 3580
[5] Face Sketch Synthesis Based on Local and Nonlocal Similarity Regularization
Tang, Songze
Zhou, Xuhuan
Zhou, Nan
Sun, Le
Wang, Jin
JOURNAL OF INFORMATION PROCESSING SYSTEMS, 2019, 15 (06): : 1449 - 1461
[6] Semi-supervised Learning for Face Sketch Synthesis in the Wild
Chen, Chaofeng
Liu, Wei
Tan, Xiao
Wong, Kwan-Yee K.
COMPUTER VISION - ACCV 2018, PT I, 2019, 11361 : 216 - 231
[7] Face Sketch Synthesis Using Regularized Broad Learning System
Li, Ping
Sheng, Bin
Chen, C. L. Philip
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 33 (10) : 5346 - 5360
[8] Face sketch synthesis: a survey
Bi, Hongbo
Liu, Ziqi
Yang, Lina
Wang, Kang
Li, Ning
MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (12) : 18007 - 18026
[9] Face sketch synthesis and recognition
Tang, XO
Wang, XG
NINTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOLS I AND II, PROCEEDINGS, 2003, : 687 - 694
[10] Face sketch synthesis: a survey
Hongbo Bi
Ziqi Liu
Lina Yang
Kang Wang
Ning Li
Multimedia Tools and Applications, 2021, 80 : 18007 - 18026

← 1 2 3 4 5 →