Human ear recognition by computer:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
London
Springer
2008
|
| Schriftenreihe: | Advances in pattern recognition
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Klappentext |
| Beschreibung: | XVIII, 201 S. Ill., graph. Darst. |
| ISBN: | 9781848001299 9781848001282 1848001282 |
Internformat
MARC
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| 020 | |a 9781848001299 |9 978-1-84800-129-9 | ||
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| 020 | |a 1848001282 |c Gb. : ca. EUR 64.15 (freier Pr.), ca. sfr 104.50 (freier Pr.) |9 1-8480-0128-2 | ||
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| 100 | 1 | |a Bhanu, Bir |d 1951- |e Verfasser |0 (DE-588)1085680223 |4 aut | |
| 245 | 1 | 0 | |a Human ear recognition by computer |c Bir Bhanu and Hui Chen |
| 264 | 1 | |a London |b Springer |c 2008 | |
| 300 | |a XVIII, 201 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Advances in pattern recognition | |
| 650 | 4 | |a Identification biométrique | |
| 650 | 4 | |a Imagerie tridimensionnelle | |
| 650 | 4 | |a Oreille externe - Identification - Informatique | |
| 650 | 4 | |a Reconnaissance des formes (Informatique) | |
| 650 | 4 | |a Datenverarbeitung | |
| 650 | 4 | |a Biometric identification | |
| 650 | 4 | |a Ear, External |x Identification |x Data processing | |
| 650 | 4 | |a Pattern recognition systems | |
| 650 | 4 | |a Three-dimensional imaging | |
| 650 | 0 | 7 | |a Ohr |0 (DE-588)4133604-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Biometrie |0 (DE-588)4124925-2 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Ohr |0 (DE-588)4133604-5 |D s |
| 689 | 0 | 1 | |a Biometrie |0 (DE-588)4124925-2 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Chen, Hui |e Verfasser |4 aut | |
| 856 | 4 | 2 | |m Digitalisierung UB Regensburg |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016274152&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 856 | 4 | 2 | |m Digitalisierung UB Regensburg |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016274152&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |3 Klappentext |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-016274152 | ||
Datensatz im Suchindex
| _version_ | 1804137314224439296 |
|---|---|
| adam_text | Contents
Preface
..........................................................
V
List of Tables
.................................................... XIII
List of Figures
...................................................
XV
1
Introduction
................................................. 1
1.1
Ear Biometrics and History
................................
I
1.2
2D and
3D
Ear Biometrics
................................. 3
1.3 3D
Ear Databases
........................................ 3
1.3.1
The UCR
Dataset
.................................. 4
1.3.2
The
UND
Dataset..................................
4
1.4
Major Ideas Presented in the Book
.......................... 5
1.5
Organization of the Book
.................................. 8
2
Ear Detection and Recognition in 2D and
3D.................... 11
2.1
2D Ear Biometrics
........................................ 12
2.2 3D
Biometrics
........................................... 13
2.2.1
Biometrics Object Detection
......................... 13
2.2.2
Biometrics Object Recognition
....................... 14
2.3 3D
Object Recognition
.................................... 16
2.3.1 3D
Object Recognition Using Surface Signatures
....... 16
2.3.2
Rapid
3D
Object Recognition
........................ 18
2.4
Conclusions
............................................. 19
3 3D
Ear Detection from Side Face Range Images
................. 21
3.1 3D
Ear Detection Using Only Range Images
.................. 21
3.1.1
Template Matching Based Detection
.................. 22
3.1.2
Reference Shape Model Based Ear Detection
........... 28
3.1.3
Experimental Results
............................... 34
3.2 3D
Ear Detection Using Range and Color Images
.............. 37
X
Contents
3.2.1 Regions-of-Interest (ROIs)
Extraction.................
39
3.2.2
Reference Ear Shape Model
......................... 49
3.2.3
Alignment of the Reference Ear Shape Model
with a Region-of-Interest
............................ 49
3.2.4
Experimental Results
............................... 53
3.3
Conclusions
............................................. 59
4
Recognizing
3D
Ears Using Ear Helix/Anti-Helix
................ 61
4.1
Ear Helix/Anti-Helix Representation
........................ 61
4.2
Surface Matching
........................................ 63
4.2.1
Coarse Alignment
.................................. 63
4.2.2
Fine Alignment
.................................... 64
4.3
Experimental Results
..................................... 65
4.3.1
Identification Performance
.......................... 67
4.3.2
Verification Performance
............................ 71
4.4
Conclusions
............................................. 81
5
Recognizing
3D
Ears Using Local Surface Patches
............... 83
5.1
Local Surface Patch Representation (LSP)
.................... 83
5.1.1
Definition of LSP
.................................. 85
5.1.2
Comparing Local Surface Patches
.................... 89
5.1.3
Generating Parameters of LSP
....................... 91
5.1.4
Invariance
of Local Surface Patches to Rigid
Transformation
.................................... 97
5.1.5
Robustness of Local Surface Patches in the Presence
of Noise
.......................................... 97
5.1.6
Comparison with Spin Image Representation
........... 101
5.2
Surface Matching
........................................ 101
5.2.1
Grouping Corresponding Pairs of LSPs
................ 101
5.2.2
Alignment of Gallery with Probe Ears
................. 102
5.3
Experimental Results
..................................... 102
5.3.1
Identification Performance
.......................... 105
5.3.2
Verification Performance
............................ 107
5.3.3
Evaluation of Verification Performance
................ 107
5.3.4
Comparison of LSP and Spin Image Representations
.... 116
5.3.5
Identification and Verification Performance with Occlusion
117
5.4
Comparison with Yan and Bowyer s Approach
................ 117
5.5
Conclusions
............................................. 121
6
Rapid
3D
Ear Indexing and Recognition
........................ 123
6.1
Introduction
............................................. 123
6.2
Indexing Approach
....................................... 124
6.3
Local Surface Patch Representation
......................... 126
6.3.1
Feature Embedding
................................ 126
6.3.2
Ranking the Hypotheses Using
S
VM..................
131
Contents
XI
6.4
Verification
.............................................. 132
6.5
Experimental Results
..................................... 133
6.5.1
Dimensionality of the Embedding
.................... 133
6.5.2
Correspondence Using the Geometric Constraints
....... 133
6.5.3
SVM Rank Learning Algorithm
...................... 138
6.5.4
Indexing and Recognition Results
.................... 138
6.5.5
Effect of Feature Embedding
........................ 139
6.5.6
Comparison of the Proposed Appraoch
with Geometric Hashing
............................ 144
6.6
Conclusions
............................................. 144
7
Performance Prediction of a
3D
Ear
Recognition System
.......................................... 147
7.1
Introduction
............................................. 147
7.2
Performance Prediction
................................... 148
7.3
Experimental Results
..................................... 153
7.3.1
Performance Prediction on
52
Pair Images
............. 153
7.3.2
Performance Prediction on
155
Pair Images
............ 153
7.4
Conclusions
............................................. 154
8
Applications of the Proposed Techniques
........................ 155
8.1
LSP Representation for General
3D
Object Recognition
........ 155
8.1.1
Local Surface Patch
................................ 155
8.1.2
Hash Table Building
............................... 159
8.1.3
Hypotheses Generation
............................. 159
8.1.4
Verification
....................................... 161
8.1.5
Experimental Results
............................... 163
8.1.6
Comparison with the Spin Image and the Spherical Spin
Image Representations
.............................. 176
8.1.7
Discussions
....................................... 176
8.2
Global-to-Local Non-Rigid Shape Registration
................ 177
8.2.1
Global Similarity Registration
....................... 178
8.2.2
Local Deformation
................................. 179
8.2.3
Experimental Results on Binary Images
............... 187
8.2.4
Experimental Results on Gray-Level Images
........... 187
8.2.5
Discussions
....................................... 188
8.3
Conclusions
............................................. 188
9
Summary and Future Work
................................... 189
9.1
Summary
............................................... 189
9.2
Future Work
............................................. 191
References
....................................................... 193
Index
........................................................... 199
Biometrics deals with recognition of individuals based on their physiological
or behavioral characteristics.The human ear
¡s a
new
biometrie
feature that
has several merits over the more common face, fingerprint and iris
biometrics. Unlike the fingerprint and iris, it can be easily captured from a
distance without a fully cooperative subject, although sometimes it may be
hidden with hair, scarf and jewellery. Also, unlike a face, the ear is a relatively
stable structure that does not change much with the age and facial
expressions.
Human Ear Recognition by Computer is the first book on the automatic
recognition of human ears.lt presents an entire range of computational
algorithms for recognition of humans by their ears. These algorithms have
been tested and validated on the largest databases that are available today.
Specific algorithms addressed include:
%
Ear helix/anti-helix based representation
#
Global-to-local registration
#
Ear recognition using helix/anti-helix representation
φ
Ear recognition using the local surface patch representation
φ
Efficient ear indexing and recognition
φ
Performance prediction for
3D
ear recognition
#
Generality and applications in computer vision and pattern recognition
This state-of-the-art research reference explores all aspects of
3D
ear
recognition, including representation, detection, recognition, indexing and
performance prediction. It has been written for a professional audience of
both researchers and practitioners within industry,and is also ideal as an
informative text for graduate students in computer science and engineering.
Professor
Bir
Bhanu has been director of the Visualization and Intelligent
Systems Laboratory (at the University of California at Riverside) since
1991
and serves as the founding Director for the Center for Research in Intelligent
Systems. He also has considerable experience working within industry and is
the successful author of several books. He is a Fellow of IEEE, AAAS,IAPR,
SPIE
and was a Senior Fellow at Honeywell Inc.
Dr.
Hui
Chen works alongside Professor Bhanu and has worked for Siemens
Medica!
solutions and the Chinese Academy of Sciences.
|
| adam_txt |
Contents
Preface
.
V
List of Tables
. XIII
List of Figures
.
XV
1
Introduction
. 1
1.1
Ear Biometrics and History
.
I
1.2
2D and
3D
Ear Biometrics
. 3
1.3 3D
Ear Databases
. 3
1.3.1
The UCR
Dataset
. 4
1.3.2
The
UND
Dataset.
4
1.4
Major Ideas Presented in the Book
. 5
1.5
Organization of the Book
. 8
2
Ear Detection and Recognition in 2D and
3D. 11
2.1
2D Ear Biometrics
. 12
2.2 3D
Biometrics
. 13
2.2.1
Biometrics Object Detection
. 13
2.2.2
Biometrics Object Recognition
. 14
2.3 3D
Object Recognition
. 16
2.3.1 3D
Object Recognition Using Surface Signatures
. 16
2.3.2
Rapid
3D
Object Recognition
. 18
2.4
Conclusions
. 19
3 3D
Ear Detection from Side Face Range Images
. 21
3.1 3D
Ear Detection Using Only Range Images
. 21
3.1.1
Template Matching Based Detection
. 22
3.1.2
Reference Shape Model Based Ear Detection
. 28
3.1.3
Experimental Results
. 34
3.2 3D
Ear Detection Using Range and Color Images
. 37
X
Contents
3.2.1 Regions-of-Interest (ROIs)
Extraction.
39
3.2.2
Reference Ear Shape Model
. 49
3.2.3
Alignment of the Reference Ear Shape Model
with a Region-of-Interest
. 49
3.2.4
Experimental Results
. 53
3.3
Conclusions
. 59
4
Recognizing
3D
Ears Using Ear Helix/Anti-Helix
. 61
4.1
Ear Helix/Anti-Helix Representation
. 61
4.2
Surface Matching
. 63
4.2.1
Coarse Alignment
. 63
4.2.2
Fine Alignment
. 64
4.3
Experimental Results
. 65
4.3.1
Identification Performance
. 67
4.3.2
Verification Performance
. 71
4.4
Conclusions
. 81
5
Recognizing
3D
Ears Using Local Surface Patches
. 83
5.1
Local Surface Patch Representation (LSP)
. 83
5.1.1
Definition of LSP
. 85
5.1.2
Comparing Local Surface Patches
. 89
5.1.3
Generating Parameters of LSP
. 91
5.1.4
Invariance
of Local Surface Patches to Rigid
Transformation
. 97
5.1.5
Robustness of Local Surface Patches in the Presence
of Noise
. 97
5.1.6
Comparison with Spin Image Representation
. 101
5.2
Surface Matching
. 101
5.2.1
Grouping Corresponding Pairs of LSPs
. 101
5.2.2
Alignment of Gallery with Probe Ears
. 102
5.3
Experimental Results
. 102
5.3.1
Identification Performance
. 105
5.3.2
Verification Performance
. 107
5.3.3
Evaluation of Verification Performance
. 107
5.3.4
Comparison of LSP and Spin Image Representations
. 116
5.3.5
Identification and Verification Performance with Occlusion
117
5.4
Comparison with Yan and Bowyer's Approach
. 117
5.5
Conclusions
. 121
6
Rapid
3D
Ear Indexing and Recognition
. 123
6.1
Introduction
. 123
6.2
Indexing Approach
. 124
6.3
Local Surface Patch Representation
. 126
6.3.1
Feature Embedding
. 126
6.3.2
Ranking the Hypotheses Using
S
VM.
131
Contents
XI
6.4
Verification
. 132
6.5
Experimental Results
. 133
6.5.1
Dimensionality of the Embedding
. 133
6.5.2
Correspondence Using the Geometric Constraints
. 133
6.5.3
SVM Rank Learning Algorithm
. 138
6.5.4
Indexing and Recognition Results
. 138
6.5.5
Effect of Feature Embedding
. 139
6.5.6
Comparison of the Proposed Appraoch
with Geometric Hashing
. 144
6.6
Conclusions
. 144
7
Performance Prediction of a
3D
Ear
Recognition System
. 147
7.1
Introduction
. 147
7.2
Performance Prediction
. 148
7.3
Experimental Results
. 153
7.3.1
Performance Prediction on
52
Pair Images
. 153
7.3.2
Performance Prediction on
155
Pair Images
. 153
7.4
Conclusions
. 154
8
Applications of the Proposed Techniques
. 155
8.1
LSP Representation for General
3D
Object Recognition
. 155
8.1.1
Local Surface Patch
. 155
8.1.2
Hash Table Building
. 159
8.1.3
Hypotheses Generation
. 159
8.1.4
Verification
. 161
8.1.5
Experimental Results
. 163
8.1.6
Comparison with the Spin Image and the Spherical Spin
Image Representations
. 176
8.1.7
Discussions
. 176
8.2
Global-to-Local Non-Rigid Shape Registration
. 177
8.2.1
Global Similarity Registration
. 178
8.2.2
Local Deformation
. 179
8.2.3
Experimental Results on Binary Images
. 187
8.2.4
Experimental Results on Gray-Level Images
. 187
8.2.5
Discussions
. 188
8.3
Conclusions
. 188
9
Summary and Future Work
. 189
9.1
Summary
. 189
9.2
Future Work
. 191
References
. 193
Index
. 199
Biometrics deals with recognition of individuals based on their physiological
or behavioral characteristics.The human ear
¡s a
new
biometrie
feature that
has several merits over the more common face, fingerprint and iris
biometrics. Unlike the fingerprint and iris, it can be easily captured from a
distance without a fully cooperative subject, although sometimes it may be
hidden with hair, scarf and jewellery. Also, unlike a face, the ear is a relatively
stable structure that does not change much with the age and facial
expressions.
Human Ear Recognition by Computer is the first book on the automatic
recognition of human ears.lt presents an entire range of computational
algorithms for recognition of humans by their ears. These algorithms have
been tested and validated on the largest databases that are available today.
Specific algorithms addressed include:
%
Ear helix/anti-helix based representation
#
Global-to-local registration
#
Ear recognition using helix/anti-helix representation
φ
Ear recognition using the local surface patch representation
φ
Efficient ear indexing and recognition
φ
Performance prediction for
3D
ear recognition
#
Generality and applications in computer vision and pattern recognition
This state-of-the-art research reference explores all aspects of
3D
ear
recognition, including representation, detection, recognition, indexing and
performance prediction. It has been written for a professional audience of
both researchers and practitioners within industry,and is also ideal as an
informative text for graduate students in computer science and engineering.
Professor
Bir
Bhanu has been director of the Visualization and Intelligent
Systems Laboratory (at the University of California at Riverside) since
1991
and serves as the founding Director for the Center for Research in Intelligent
Systems. He also has considerable experience working within industry and is
the successful author of several books. He is a Fellow of IEEE, AAAS,IAPR,
SPIE
and was a Senior Fellow at Honeywell Inc.
Dr.
Hui
Chen works alongside Professor Bhanu and has worked for Siemens
Medica!
solutions and the Chinese Academy of Sciences. |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Bhanu, Bir 1951- Chen, Hui |
| author_GND | (DE-588)1085680223 |
| author_facet | Bhanu, Bir 1951- Chen, Hui |
| author_role | aut aut |
| author_sort | Bhanu, Bir 1951- |
| author_variant | b b bb h c hc |
| building | Verbundindex |
| bvnumber | BV023071006 |
| callnumber-first | T - Technology |
| callnumber-label | TK7882 |
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| callnumber-search | TK7882.P3 |
| callnumber-sort | TK 47882 P3 |
| callnumber-subject | TK - Electrical and Nuclear Engineering |
| classification_rvk | SK 850 ST 277 ST 330 |
| ctrlnum | (OCoLC)180478674 (DE-599)DNB98596393X |
| dewey-full | 006.4 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.4 |
| dewey-search | 006.4 |
| dewey-sort | 16.4 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik Mathematik |
| discipline_str_mv | Informatik Mathematik |
| format | Book |
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| id | DE-604.BV023071006 |
| illustrated | Illustrated |
| index_date | 2024-07-02T19:33:02Z |
| indexdate | 2024-07-09T21:10:19Z |
| institution | BVB |
| isbn | 9781848001299 9781848001282 1848001282 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016274152 |
| oclc_num | 180478674 |
| open_access_boolean | |
| owner | DE-703 DE-355 DE-BY-UBR |
| owner_facet | DE-703 DE-355 DE-BY-UBR |
| physical | XVIII, 201 S. Ill., graph. Darst. |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Springer |
| record_format | marc |
| series2 | Advances in pattern recognition |
| spelling | Bhanu, Bir 1951- Verfasser (DE-588)1085680223 aut Human ear recognition by computer Bir Bhanu and Hui Chen London Springer 2008 XVIII, 201 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Advances in pattern recognition Identification biométrique Imagerie tridimensionnelle Oreille externe - Identification - Informatique Reconnaissance des formes (Informatique) Datenverarbeitung Biometric identification Ear, External Identification Data processing Pattern recognition systems Three-dimensional imaging Ohr (DE-588)4133604-5 gnd rswk-swf Biometrie (DE-588)4124925-2 gnd rswk-swf Ohr (DE-588)4133604-5 s Biometrie (DE-588)4124925-2 s DE-604 Chen, Hui Verfasser aut Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016274152&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016274152&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Bhanu, Bir 1951- Chen, Hui Human ear recognition by computer Identification biométrique Imagerie tridimensionnelle Oreille externe - Identification - Informatique Reconnaissance des formes (Informatique) Datenverarbeitung Biometric identification Ear, External Identification Data processing Pattern recognition systems Three-dimensional imaging Ohr (DE-588)4133604-5 gnd Biometrie (DE-588)4124925-2 gnd |
| subject_GND | (DE-588)4133604-5 (DE-588)4124925-2 |
| title | Human ear recognition by computer |
| title_auth | Human ear recognition by computer |
| title_exact_search | Human ear recognition by computer |
| title_exact_search_txtP | Human ear recognition by computer |
| title_full | Human ear recognition by computer Bir Bhanu and Hui Chen |
| title_fullStr | Human ear recognition by computer Bir Bhanu and Hui Chen |
| title_full_unstemmed | Human ear recognition by computer Bir Bhanu and Hui Chen |
| title_short | Human ear recognition by computer |
| title_sort | human ear recognition by computer |
| topic | Identification biométrique Imagerie tridimensionnelle Oreille externe - Identification - Informatique Reconnaissance des formes (Informatique) Datenverarbeitung Biometric identification Ear, External Identification Data processing Pattern recognition systems Three-dimensional imaging Ohr (DE-588)4133604-5 gnd Biometrie (DE-588)4124925-2 gnd |
| topic_facet | Identification biométrique Imagerie tridimensionnelle Oreille externe - Identification - Informatique Reconnaissance des formes (Informatique) Datenverarbeitung Biometric identification Ear, External Identification Data processing Pattern recognition systems Three-dimensional imaging Ohr Biometrie |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016274152&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016274152&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT bhanubir humanearrecognitionbycomputer AT chenhui humanearrecognitionbycomputer |