Holdings: Learning based robot vision

Learning based robot vision: principles and applications

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Bibliographic Details
Main Author:	Pauli, Josef (Author)
Format:	Book
Language:	English
Published:	Berlin [u.a.] Springer 2001
Series:	Lecture notes in computer science 2048
Subjects:	Robots - Commande, Systèmes de Robots - Systèmes de commande Vision artificielle (Robotique) Vision artificielle (robotique) agent intelligent apprentissage machine reconnaissance objet robot mobile vision robot Robot vision Robots > Control systems Autonomer Roboter Problemlösen Objekterkennung Maschinelles Lernen Monitorüberwachung Maschinelles Sehen
Online Access:	Inhaltsverzeichnis
Physical Description:	IX, 288 S. Ill., graph. Darst.
ISBN:	3540421084

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MARC


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Record in the Search Index

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adam_text	CONTENTS 1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 NEED FOR NEW-GENERATION ROBOT SYSTEMS . . . . . . . . . . . . . . . . . . 1 1.2 PARADIGMS OF COMPUTER VISION (CV) AND ROBOT VISION (RV) . 5 1.2.1 CHARACTERIZATION OF COMPUTER VISION . . . . . . . . . . . . . . . 5 1.2.2 CH ARACTERIZATION OF ROBOT VISION . . . . . . . . . . . . . . . . . . . 8 1.3 ROBOT SYSTEMS VERSUS AUTONOMOUS ROBOT SYSTEMS . . . . . . . . . 10 1.3.1 CHARACTERIZATION OF A ROBOT SYSTEM . . . . . . . . . . . . . . . . 10 1.3.2 CHARACTERIZATION OF AN AUTONOMOUS ROBOT SYSTEM. . . . 11 1.3.3 AUTONOMOUS CAMERA-EQUIPPED ROBOT SYSTEM . . . . . . . 14 1.4 IMPORTANT ROLE OF DEMONSTRATION AND LEARNING . . . . . . . . . . . . 15 1.4.1 LEARNING FEATURE COMPATIBILITIES UNDER REAL IMAGING . 15 1.4.2 LEARNING FEATURE MANIFOLDS OF REAL WORLD SITUATIONS . 18 1.4.3 LEARNING ENVIRONMENT-EFFECTOR-IMAGE RELATIONSHIPS . . 20 1.4.4 COMPATIBILITIES, MANIFOLDS, AND RELATIONSHIPS . . . . . . . . 21 1.5 CH APTER OVERVIEW OF TH E WORK . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2. COMPATIBILITIES FOR OBJECT BOUNDARY DETECTION . . . . . . . . . . . 25 2.1 INTRODUCTION TO TH E CH APTER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 2.1.1 GENERAL CONTEXT OF TH E CH APTER . . . . . . . . . . . . . . . . . . . . 25 2.1.2 OBJECT LOCALIZATION AND BOUNDARY EXTRACTION. . . . . . . . 27 2.1.3 DETAILED REVIEW OF RELEVANT LITERATURE . . . . . . . . . . . . . . 28 2.1.4 OUTLINE OF TH E SECTIONS IN TH E CH APTER . . . . . . . . . . . . . . 31 2.2 GEOMETRIC/PHOTOMETRIC COMPATIBILITY PRINCIPLES . . . . . . . . . . . 32 2.2.1 HOUGHTRANSFORMATION FOR LINE EXTRACTION. . . . . . . . . . . 32 2.2.2 ORIENTATION COMPATIBILITY BETWEEN LINES AND EDGES . . 34 2.2.3 JUNCTION COMPATIBILITY BETWEEN PENCILS AND CORNERS . . 41 2.3 COMPATIBILITY-BASED STRUCTURAL LEVEL GROUPING . . . . . . . . . . . . 46 2.3.1 HOUGHPEAKS FOR APPROXIMATE PARALLEL LINES . . . . . . . . . 47 2.3.2 PHASE COMPATIBILITY BETWEEN PARALLELS AND RAMPS . . . . 49 2.3.3 EXTRACTION OF REGULAR QUADRANGLES . . . . . . . . . . . . . . . . . 54 2.3.4 EXTRACTION OF REGULAR POLYGONS . . . . . . . . . . . . . . . . . . . . 61 2.4 COMPATIBILITY-BASED ASSEMBLY LEVEL GROUPING . . . . . . . . . . . . . 69 2.4.1 FOCUSING IMAGE PROCESSING ON POLYGONAL WINDOWS . . . . 70 2.4.2 VANISHING-POINT COMPATIBILITY OF PARALLEL LINES . . . . . . 74 VIII CONTENTS 2.4.3 PENCIL COMPATIBILITY OF MEETING BOUNDARY LINES . . . . . 76 2.4.4 BOUNDARY EXTRACTION FOR APPROXIMATE POLYHEDRA . . . . . 78 2.4.5 GEOMETRIC REASONING FOR BOUNDARY EXTRACTION . . . . . . . 79 2.5 VISUAL DEMONSTRATIONS FOR LEARNING DEGREES OF COMPATIBILITY . 85 2.5.1 LEARNING DEGREE OF LINE/EDGE ORIENTATION COMPATIBILITY 85 2.5.2 LEARNING DEGREE OF PARALLEL/RAMPPHASE COMPATIBILITY . 90 2.5.3 LEARNING DEGREE OF PARALLELISM COMPATIBILITY . . . . . . . . 95 2.6 SUMMARY AND DISCUSSION OF TH E CH APTER . . . . . . . . . . . . . . . . . . 96 3. MANIFOLDS FOR OBJECT AND SITUATION RECOGNITION . . . . . . . . . . 101 3.1 INTRODUCTION TO TH E CH APTER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 3.1.1 GENERAL CONTEXT OF TH E CH APTER . . . . . . . . . . . . . . . . . . . . 101 3.1.2 APPROACHFOR OBJECT AND SITUATION RECOGNITION . . . . . . 102 3.1.3 DETAILED REVIEW OF RELEVANT LITERATURE . . . . . . . . . . . . . . 103 3.1.4 OUTLINE OF TH E SECTIONS IN TH E CH APTER . . . . . . . . . . . . . . 108 3.2 LEARNING PATTERN MANIFOLDS WITHGBFS AND PCA . . . . . . . . . . . 108 3.2.1 COMPATIBILITY AND DISCRIMINABILITY FOR RECOGNITION . . . 108 3.2.2 REGULARIZATION PRINCIPLES AND GBF NETWORKS . . . . . . . . 111 3.2.3 CANONICAL FRAMES WITHPRINCIPAL COMPONENT ANALYSIS . 116 3.3 GBF NETWORKS FOR APPROXIMATION OF RECOGNITION FUNCTIONS . . 122 3.3.1 APPROACHOF GBF NETWORK LEARNING FOR RECOGNITION . . 122 3.3.2 OBJECT RECOGNITION UNDER ARBITRARY VIEW ANGLE . . . . . 124 3.3.3 OBJECT RECOGNITION FOR ARBITRARY VIEW DISTANCE . . . . . . 129 3.3.4 SCORING OF GRASPING SITUATIONS . . . . . . . . . . . . . . . . . . . . . 131 3.4 SOPHISTICATED MANIFOLD APPROXIMATION FOR ROBUST RECOGNITION . 133 3.4.1 MAKING MANIFOLD APPROXIMATION TRACTABLE . . . . . . . . . . 134 3.4.2 LOG-POLAR TRANSFORMATION FOR MANIFOLD SIMPLIFICATION . 137 3.4.3 SPACE-TIME CORRELATIONS FOR MANIFOLD REFINEMENT . . . . 145 3.4.4 LEARNING STRATEGY WITHPCA/GBF MIXTURES . . . . . . . . . 154 3.5 SUMMARY AND DISCUSSION OF TH E CH APTER . . . . . . . . . . . . . . . . . . 168 4. LEARNING-BASED ACHIEVEMENT OF RV COMPETENCES . . . . . . . . 171 4.1 INTRODUCTION TO TH E CH APTER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 4.1.1 GENERAL CONTEXT OF TH E CH APTER . . . . . . . . . . . . . . . . . . . . 171 4.1.2 LEARNING BEH AVIOR-BASED SYSTEMS . . . . . . . . . . . . . . . . . . 174 4.1.3 DETAILED REVIEW OF RELEVANT LITERATURE . . . . . . . . . . . . . . 178 4.1.4 OUTLINE OF TH E SECTIONS IN TH E CH APTER . . . . . . . . . . . . . . 182 4.2 INTEGRATING DELIBERATE STRATEGIES AND VISUAL FEEDBACK . . . . . . . 183 4.2.1 DYNAMICAL SYSTEMS AND CONTROL MECHANISMS . . . . . . . . 183 4.2.2 GENERIC MODULES FOR SYSTEM DEVELOPMENT . . . . . . . . . . . 197 4.3 TREATMENT OF AN EXEMPLARY HIGH-LEVEL TASK . . . . . . . . . . . . . . . 206 4.3.1 DESCRIPTION OF AN EXEMPLARY HIGH-LEVEL TASK . . . . . . . . 206 4.3.2 LOCALIZATION OF A TARGET OBJECT IN THE IMAGE . . . . . . . . . 208 4.3.3 DETERMINING AND RECONSTRUCTING OBSTACLE OBJECTS . . . . 213 4.3.4 APPROACHING AND GRASPING OBSTACLE OBJECTS . . . . . . . . . 219 CONTENTS IX 4.3.5 CLEARING AWAY OBSTACLE OBJECTS ON A PARKING AREA . . . 225 4.3.6 INSPECTION AND/OR MANIPULATION OF A TARGET OBJECT . . . 231 4.3.7 MONITORING THE TASK-SOLVING PROCESS . . . . . . . . . . . . . . . . 237 4.3.8 OVERALL TASK-SPECIFIC CONFIGURATION OF MODULES. . . . . . . 238 4.4 BASIC MECHANISMS FOR CAMERAROBOT COORDINATION . . . . . . . . . 240 4.4.1 CAMERAMANIPULATOR RELATION FOR ONE-STEP CONTROL . . 240 4.4.2 CAMERA*MANIPULATOR RELATION FOR MULTI-STEP CONTROL . 245 4.4.3 HAND SERVOING FOR DETERMINING THE OPTICAL AXIS . . . . . 248 4.4.4 DETERMINING TH E FIELD OF SH ARP VIEW . . . . . . . . . . . . . . . 250 4.5 SUMMARY AND DISCUSSION OF TH E CH APTER . . . . . . . . . . . . . . . . . . 252 5. SUMMARY AND DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 5.1 DEVELOPING CAMERA-EQUIPPED ROBOT SYSTEMS . . . . . . . . . . . . . . 255 5.2 RATIONALE FOR TH E CONTENTS OF TH IS WORK . . . . . . . . . . . . . . . . . . 258 5.3 PROPOSALS FOR FUTURE RESEARCH TOPICS . . . . . . . . . . . . . . . . . . . . . 260 APPENDIX 1: ELLIPSOIDAL INTERPOLATION . . . . . . . . . . . . . . . . . . . . . . . . . 263 APPENDIX 2: FURTHER BEHAVIORAL MODULES . . . . . . . . . . . . . . . . . . . . . 265 SYMBOLS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 INDEX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277
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series	Lecture notes in computer science
series2	Lecture notes in computer science
spelling	Pauli, Josef Verfasser aut Learning based robot vision principles and applications Josef Pauli Berlin [u.a.] Springer 2001 IX, 288 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Lecture notes in computer science 2048 Robots - Commande, Systèmes de Robots - Systèmes de commande ram Vision artificielle (Robotique) Vision artificielle (robotique) ram agent intelligent inriac apprentissage machine inriac reconnaissance objet inriac robot mobile inriac vision robot inriac Robot vision Robots Control systems Autonomer Roboter (DE-588)4304075-5 gnd rswk-swf Problemlösen (DE-588)4076358-4 gnd rswk-swf Objekterkennung (DE-588)4314334-9 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Monitorüberwachung (DE-588)4291501-6 gnd rswk-swf Maschinelles Sehen (DE-588)4129594-8 gnd rswk-swf Autonomer Roboter (DE-588)4304075-5 s Maschinelles Sehen (DE-588)4129594-8 s Monitorüberwachung (DE-588)4291501-6 s Maschinelles Lernen (DE-588)4193754-5 s Objekterkennung (DE-588)4314334-9 s Problemlösen (DE-588)4076358-4 s DE-604 Lecture notes in computer science 2048 (DE-604)BV000000607 2048 SWB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009373902&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis
spellingShingle	Pauli, Josef Learning based robot vision principles and applications Lecture notes in computer science Robots - Commande, Systèmes de Robots - Systèmes de commande ram Vision artificielle (Robotique) Vision artificielle (robotique) ram agent intelligent inriac apprentissage machine inriac reconnaissance objet inriac robot mobile inriac vision robot inriac Robot vision Robots Control systems Autonomer Roboter (DE-588)4304075-5 gnd Problemlösen (DE-588)4076358-4 gnd Objekterkennung (DE-588)4314334-9 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Monitorüberwachung (DE-588)4291501-6 gnd Maschinelles Sehen (DE-588)4129594-8 gnd
subject_GND	(DE-588)4304075-5 (DE-588)4076358-4 (DE-588)4314334-9 (DE-588)4193754-5 (DE-588)4291501-6 (DE-588)4129594-8
title	Learning based robot vision principles and applications
title_auth	Learning based robot vision principles and applications
title_exact_search	Learning based robot vision principles and applications
title_full	Learning based robot vision principles and applications Josef Pauli
title_fullStr	Learning based robot vision principles and applications Josef Pauli
title_full_unstemmed	Learning based robot vision principles and applications Josef Pauli
title_short	Learning based robot vision
title_sort	learning based robot vision principles and applications
title_sub	principles and applications
topic	Robots - Commande, Systèmes de Robots - Systèmes de commande ram Vision artificielle (Robotique) Vision artificielle (robotique) ram agent intelligent inriac apprentissage machine inriac reconnaissance objet inriac robot mobile inriac vision robot inriac Robot vision Robots Control systems Autonomer Roboter (DE-588)4304075-5 gnd Problemlösen (DE-588)4076358-4 gnd Objekterkennung (DE-588)4314334-9 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Monitorüberwachung (DE-588)4291501-6 gnd Maschinelles Sehen (DE-588)4129594-8 gnd
topic_facet	Robots - Commande, Systèmes de Robots - Systèmes de commande Vision artificielle (Robotique) Vision artificielle (robotique) agent intelligent apprentissage machine reconnaissance objet robot mobile vision robot Robot vision Robots Control systems Autonomer Roboter Problemlösen Objekterkennung Maschinelles Lernen Monitorüberwachung Maschinelles Sehen
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009373902&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
volume_link	(DE-604)BV000000607
work_keys_str_mv	AT paulijosef learningbasedrobotvisionprinciplesandapplications

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