Research on the 3D face recognition based on multi-class classifier with depth and point cloud data

被引：0

作者：

Wu, Zhuoran ^{[1
]}

Hou, Zhenjie ^{[1
]}

Zhang, Jian ^{[1
]}

机构：

[1] Changzhou Univ, Changzhou, Jiangsu, Peoples R China

来源：

PROCEEDINGS OF 2016 IEEE ADVANCED INFORMATION MANAGEMENT, COMMUNICATES, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IMCEC 2016) | 2016年

基金：

中国国家自然科学基金;

关键词：

3D face recognition; depth data; point cloud data; CAND1DE-3; face model standardization; multi-class classifier;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Human face recognition technology usually takes advantages of two-dimensional or three-dimensional data. Rising from 1980s, three-dimensional face recognition technology soon become one of the headed topic because of its admirable resistance to interference and more information compared with two-dimensional face recognition technology. The new 3D face model standardization algorithm presented in this article provides a solution to transfer the obtained face model to standardized CAND1DE-3 face model. The article also provides a new Bayesian classification model based on multi-class classifier, which could overcome the difficulty that ono-verse-one classifier has a low recognition rate when facing more than two people. The article conduct the comparison experiment based on the provided algorithm. According to the experiment, it could raise the face recognition rate efficiently when applying the standardization algorithm and training modeL

引用

页码：398 / 402

页数：5

共 50 条

[21] 3D Face Recognition Based on Hybrid Data
Li, Xinxin
Gong, Xun
[J]. ROUGH SETS, IJCRS 2019, 2019, 11499 : 454 - 464
[22] Recognition of key targets of locomotive bottom based on 3D point cloud data
Huang, Qian
Wang, Ze-yong
Li, Jin-long
Jiang, Wen-nan
Gao, Xiao-rong
[J]. PROCEEDINGS OF 2017 IEEE FAR EAST FORUM ON NONDESTRUCTIVE EVALUATION/TESTING: NEW TECHNOLOGY & APPLICATION (IEEE FENDT 2017), 2017, : 149 - 153
[23] Research on a face recognition algorithm based on 3D face data and 2D face image matching
Niu, Wenjie
Zhao, Yuankun
Yu, Zhiyan
Liu, Yu
Gong, Yu
[J]. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2023, 91
[24] Automatic Reconstruction of Dense 3D Face Point Cloud with A Single Depth Image
Zhang, Shu
Yu, Hui
Dong, Junyu
Wang, Ting
Ju, Zhaojie
Liu, Honghai
[J]. 2015 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2015): BIG DATA ANALYTICS FOR HUMAN-CENTRIC SYSTEMS, 2015, : 1439 - 1444
[25] REPRESENTING 3D FACE FROM POINT CLOUD TO FACE-ALIGNED SPHERICAL DEPTH MAP
Liu, Peijiang
Wang, Yunhong
Zhang, Zhaoxiang
[J]. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2012, 26 (01)
[26] Research on 3D Face Geometric Modeling Approach Based on Scattered-point Cloud
Shi Li-juan
Zhao Jian
Che Na
An Zhi-yong
[J]. INTERNATIONAL JOURNAL OF GRID AND DISTRIBUTED COMPUTING, 2016, 9 (11): : 111 - 118
[27] Weighted Multi-task Sparse Representation Classifier for 3D Face Recognition
Tang, Linlin
Li, Zhangyan
Qian, Tao
Qi, Shuhan
Liu, Yang
Zhang, Jiajia
Shi, Shuaijie
Liu, Churan
Su, Jingyong
[J]. ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING (ECC 2021), 2022, 268 : 105 - 116
[28] 3D face recognition using depth-based features
Shin, Hyoungchul
Sohn, Kwanghoon
[J]. PROCEEDINGS OF THE SEVENTH IASTED INTERNATIONAL CONFERENCE ON VISUALIZATION, IMAGING, AND IMAGE PROCESSING, 2007, : 241 - +
[29] 3D Face Recognition by SURF Operator Based on Depth Image
Lei Yunqi
Lai Haibin
Jiang Xutuan
[J]. PROCEEDINGS OF 2010 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY, VOL 9 (ICCSIT 2010), 2010, : 240 - 244
[30] Expression and Occlusion invariant 3D face recognition based on region classifier
Dutta, Koushik
Bhattacharjee, Debotosh
Nasipuri, Mita
[J]. 2016 1ST INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY, INFORMATION SYSTEMS AND ELECTRICAL ENGINEERING (ICITISEE), 2016, : 99 - 104

← 1 2 3 4 5 →