Face image retrieval based on shape and texture feature fusion

被引：0

作者：

Lu Z. ^{[1
]}

Yang J. ^{[1
]}

Liu Q. ^{[1
]}

机构：

[1] School of Information and Control Engineering, Nanjing University of Information Science and Technology, Nanjing

来源：

Lu, Zongguang (zongguanglu@nuist.edu.cn) | 1600年 / Tsinghua University Press卷 / 03期

关键词：

coarse-to-fine; convolutional neural networks (CNNs); face retrieval;

D O I：

10.1007/s41095-017-0091-7

中图分类号：

学科分类号：

摘要：

Humongous amounts of data bring various challenges to face image retrieval. This paper proposes an efficient method to solve those problems. Firstly, we use accurate facial landmark locations as shape features. Secondly, we utilise shape priors to provide discriminative texture features for convolutional neural networks. These shape and texture features are fused to make the learned representation more robust. Finally, in order to increase efficiency, a coarse-tofine search mechanism is exploited to efficiently find similar objects. Extensive experiments on the CASIAWebFace, MSRA-CFW, and LFW datasets illustrate the superiority of our method. © 2017, The Author(s).

引用

页码：359 / 368

页数：9

共 50 条

[1] Face image retrieval based on shape and texture feature fusion
Zongguang Lu
Jing Yang
Qingshan Liu
[J]. Computational Visual Media, 2017, 3 (04) : 359 - 368
[2] Texture Image Retrieval Based on Statistical Feature Fusion
Wang Hengbin
Qu Huaijing
[J]. ELEVENTH INTERNATIONAL CONFERENCE ON GRAPHICS AND IMAGE PROCESSING (ICGIP 2019), 2020, 11373
[3] Image retrieval using Feature Extraction based on Shape and Texture
Tharani, T.
Sundaresan, M.
[J]. SECOND INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING, 2010, 7546
[4] Smile recognition based on the fusion of the face texture feature and the mouth shape feature
Li Yuanzheng
[J]. PROCEEDINGS OF THE 2016 4TH INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS AND COMPUTING TECHNOLOGY, 2016, 60 : 1308 - 1312
[5] Fusion of Colour, Shape and Texture Features for Content Based Image Retrieval
Anantharatnasamy, Pratheep
Sriskandaraja, Kaavya
Nandakumar, Vahissan
Deegalla, Sampath
[J]. PROCEEDINGS OF THE 2013 8TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION (ICCSE 2013), 2013, : 422 - 427
[6] Trademark Image Retrieval by Integrating Shape with Texture Feature
Agrawal, Deepti
Jalal, Anand Singh
Tripathi, Rajesh
[J]. PROCEEDINGS OF THE 2013 INTERNATIONAL CONFERENCE ON INFORMATION SYSTEMS AND COMPUTER NETWORKS (ISCON), 2013, : 30 - 33
[7] Medical Image Retrieval Based on Texture and Shape Feature Co-occurrence
Zhou, Yixiao
Huang, Yan
Ling, Haibin
Peng, Jingliang
[J]. MEDICAL IMAGING 2012: COMPUTER-AIDED DIAGNOSIS, 2012, 8315
[8] Based on texture feature of color image retrieval
Lin, Jinhui
Zhang, Jixiang
[J]. MATERIALS, MECHANICAL ENGINEERING AND MANUFACTURE, PTS 1-3, 2013, 268-270 : 1748 - 1751
[9] Image Retrieval Based on Color, Shape and Texture
Gupta, Ashutosh
Gangadharappa, M.
[J]. 2015 2ND INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT (INDIACOM), 2015, : 2097 - 2104
[10] Image Retrieval Based on Shape Feature and Color Feature
Liu, Jun-ling
Zhao, Hong-Wei
Zhao, Hao-yu
Chen, Chong-xu
[J]. MATERIAL AND MANUFACTURING TECHNOLOGY II, PTS 1 AND 2, 2012, 341-342 : 560 - +

← 1 2 3 4 5 →