CN105893947B - 基于多局部相关特征学习的两视角人脸识别方法 - Google Patents
基于多局部相关特征学习的两视角人脸识别方法 Download PDFInfo
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- 238000012549 training Methods 0.000 claims abstract description 29
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
- G06F18/24147—Distances to closest patterns, e.g. nearest neighbour classification
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Abstract
Description
3Train | 4Train | 5Train | 6Train | 7Train | |
MLCFL | 97.81±2.52 | 99.13±1.06 | 99.26±1.19 | 99.67±0.83 | 99.79±0.34 |
GrMCCA | 96.72±2.39 | 99.08±0.95 | 99.57±0.65 | 99.61±0.63 | 99.65±0.68 |
LDCCA | 97.54±1.84 | 99.31±0.66 | 99.51±0.56 | 99.67±0.64 | 99.51±0.94 |
MvDA | 95.41±3.44 | 98.09±1.25 | 98.90±0.95 | 99.15±1.23 | 99.44±0.72 |
DCCA | 93.01±4.95 | 93.93±3.50 | 95.15±3.43 | 97.78±1.52 | 97.06±2.35 |
ALPCCA | 92.95±3.44 | 96.30±1.39 | 97.91±1.09 | 97.91±0.74 | 96.78±1.55 |
LPCCA | 78.80±5.09 | 80.81±5.94 | 83.25±3.12 | 69.87±6.35 | 63.22±8.73 |
3Train | 4Train | 5Train | 6Train | 7Train | |
MLCFL | 94.03±0.96 | 97.68±0.39 | 98.81±0.41 | 99.07±0.45 | 99.37±0.26 |
GrMCCA | 93.01±1.00 | 96.86±0.54 | 98.39±0.56 | 98.86±0.53 | 99.31±0.27 |
LDCCA | 93.10±1.17 | 96.83±0.48 | 98.40±0.46 | 98.89±0.48 | 99.33±0.25 |
MvDA | 93.83±0.87 | 97.53±0.41 | 98.75±0.43 | 99.04±0.50 | 99.31±0.28 |
DCCA | 93.03±1.24 | 96.76±0.52 | 98.27±0.50 | 98.74±0.49 | 99.13±0.29 |
ALPCCA | 90.19±0.77 | 95.23±0.62 | 96.96±0.57 | 98.09±0.73 | 98.82±0.30 |
LPCCA | 72.73±2.88 | 78.67±3.11 | 82.38±2.53 | 86.20±3.28 | 87.82±2.15 |
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Families Citing this family (8)
Publication number | Priority date | Publication date | Assignee | Title |
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CN106446778A (zh) * | 2016-08-27 | 2017-02-22 | 天津大学 | 基于加速度传感器的人体运动识别方法 |
CN106372629B (zh) * | 2016-11-08 | 2020-02-07 | 汉王科技股份有限公司 | 一种活体检测方法和装置 |
CN106897669B (zh) * | 2017-01-19 | 2019-12-27 | 同济大学 | 一种基于一致迭代多视角迁移学习的行人再辨识方法 |
CN107563334B (zh) * | 2017-09-07 | 2020-08-11 | 南京信息工程大学 | 基于鉴别线性表示保留投影的人脸识别方法 |
CN109685058B (zh) | 2017-10-18 | 2021-07-09 | 杭州海康威视数字技术股份有限公司 | 一种图像目标识别方法、装置及计算机设备 |
CN108446650A (zh) * | 2018-03-27 | 2018-08-24 | 百度在线网络技术(北京)有限公司 | 用于识别人脸的方法和装置 |
CN108830163B (zh) * | 2018-05-21 | 2021-11-09 | 西京学院 | 一种基于局部判别cca的海关身份验证***及方法 |
CN111611963B (zh) * | 2020-05-29 | 2023-12-26 | 扬州大学 | 一种基于近邻保持典型相关分析的人脸识别方法 |
Citations (3)
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US6922494B1 (en) * | 1999-09-24 | 2005-07-26 | Eye Web, Inc. | Automated image scaling |
CN103473529A (zh) * | 2013-08-26 | 2013-12-25 | 昆明学院 | 一种多视角取像人脸识别的方法及装置 |
CN104090885A (zh) * | 2013-12-09 | 2014-10-08 | 武汉飞凌视讯科技有限公司 | 一种基于局部拷贝检测的多视角视频对象检索***及方法 |
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US6922494B1 (en) * | 1999-09-24 | 2005-07-26 | Eye Web, Inc. | Automated image scaling |
CN103473529A (zh) * | 2013-08-26 | 2013-12-25 | 昆明学院 | 一种多视角取像人脸识别的方法及装置 |
CN104090885A (zh) * | 2013-12-09 | 2014-10-08 | 武汉飞凌视讯科技有限公司 | 一种基于局部拷贝检测的多视角视频对象检索***及方法 |
Non-Patent Citations (1)
Title |
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结合奇异值和形态学的人脸特征提取;刘艳艳 等;《现代计算机(专业版)》;20130815(第23期);第16-19页 * |
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