Real-time detection of pedestrians from a moving vehicle using thermophile and radar sensor fusion:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
Düsseldorf
VDI-Verl.
2006
|
| Ausgabe: | Als Ms. gedr. |
| Schriftenreihe: | Fortschritt-Berichte VDI
Reihe 12, Verkehrstechnik/Fahrzeugtechnik ; Nr. 628 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | VIII, 166 S. Ill., graph. Darst. |
| ISBN: | 3183628120 |
Internformat
MARC
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| 100 | 1 | |a Linzmeier, Dirk |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Real-time detection of pedestrians from a moving vehicle using thermophile and radar sensor fusion |c Dirk Linzmeier |
| 250 | |a Als Ms. gedr. | ||
| 264 | 1 | |a Düsseldorf |b VDI-Verl. |c 2006 | |
| 300 | |a VIII, 166 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a Fortschritt-Berichte VDI : Reihe 12, Verkehrstechnik/Fahrzeugtechnik |v Nr. 628 | |
| 502 | |a Zugl.: Ulm, Univ., Diss. | ||
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Datensatz im Suchindex
| DE-BY-862_location | 2801 |
|---|---|
| DE-BY-FWS_call_number | 2900/07207 |
| DE-BY-FWS_katkey | 716114 |
| DE-BY-FWS_media_number | 083000508816 |
| _version_ | 1824553811283279873 |
| adam_text | 1 Introduction 1
2 State of the Art 5
2.1 Pedestrian Detection Systems 5
2.1.1 Market Aspects 5
2.1.2 Vision Based Systems 6
2.1.3 Infrared Camera Systems 8
2.1.4 Systems Based on Laserscanners 10
2.1.5 Radar Systems 11
2.1.6 Pyroelectric Sensor Systems 12
2.1.7 Pedestrian Detection with Thermopiles 13
2.1.8 Multiple Sensor Systems 14
2.1.9 Collision Assessment 15
2.2 Pedestrian Protecrion Related Issues 16
2.2.1 Legal Regulations 16
2.2.2 Accident Statistics 17
2.3 Discussion 18
3 Sensor and System Description 20
3.1 System Setup 20
3.2 Thermopiles 21
3.2.1 Detector Parameters 24
3.3 Radar Sensor 25
3.3.1 Characteristics 25
3.3.2 Localization 27
3.3.3 SpecificationoftheUtilized Sensors 29
3.4 Data Communication 29
4 Physical Fundamentals of Infrared Detection 32
4.1 Infrared Radiation 32
4.2 Radiometry 33
4.3 Atmospheric Transmission 37
4.3.1 Absorption 38
4.3.2 Scattering 38
4.4 Principles of Infrared Detection 40
5 Thermopile Pedestrian Detection System 42
5.1 Thermopile System Design 42
5.2 Sensor Arrangement for 2 D Position Estimation 43
5.2.1 Object Localization 44
5.2.2 Sensor Arrangement Requirements 45
5.2.3 Positioning Parameters 46
5.2.4 Complexity of the Sensor Arrangement 47
5.2.5 Grid Based Optimization 48
5.2.6 Simulated Annealing 50
5.2.7 Objective function 52
5.2.8 Results 55
5.3 Sensor Arrangement Calibration 56
5.3.1 Calibration Procedure 56
5.3.2 Position and Alignment Computation 58
5.4 Probabilistic Signal Processing Methods 59
5.4.1 Preprocessing of the Thermopile Signals 60
5.4.2 Thermopile Signal Interpretation 61
5.4.3 Probability Fusion 69
5.5 Position estimation with Occupancy Grid 73
5.5.1 Occupancy Grid Method 73
5.5.2 Grid Update 75
5.6 Segmentation 80
5.7 Benefit of Incorporating Radar Sensors into the System 83
5.7.1 Classification 83
6 Thermopile and Radar Sensor Data Fusion 86
6.1 Sensor Fusion Architectures 87
6.1.1 Architectures in Comparison 89
6.1.2 Thermopile and Radar Sensor Fusion Architecture 90
6.2 Multiple Target, Multiple Sensor Tracking 93
6.2.1 Overview of the Tracking Process 93
6.2.2 Kaiman Filtering and Prediction 95
6.2.3 Data Association 99
6.2.4 Sensor Target Fusion 101
6.2.5 Ego morJon Compensation 102
6.3 Fusion of Classification Results 105
6.3.1 Object Types 105
6.3.2 Dempster ShaferTheory(DST) 107
6.3.3 Comparison ofBayesian and Dempster Shafer Fusion Techniques . 111
6.3.4 Implementation of the Object Type Fusion 114
7 Collision Assessment 119
7.1 Situation Analysis Trigger Algorithm 119
7.1.1 Dimension of the Triggering Region in Longitudinal Direction ... 120
7.1.2 Sizeofthe Triggering Region in Lateral Direction 122
7.2 Crash Relevant Target Filter and Decision Algorithm 123
7.2.1 Temporal Position Reconstruction of the Pedestrian 124
7.2.2 Tempora] Reconstruction of the Thermopile Signal 124
7.2.3 Comparison of the Theoretical and Actual Thermopile Signals ... 127
8 Tests and Results 129
8.1 Statistical Evaluation of Classifiers 129
8.2 Generation of the Measurement Data Base 132
8.3 Quantitative System Analysis 133
8.4 Qualitative System Analysis 139
9 Conclusions 141
A Notation 143
B Calculations and Proofs 147
B.l Bayesian Inference 147
B.2 SimilarityofBayesandDST 147
B.3 Implementation of the SWF 148
B.4 Process and Measurement Noise Matrix 149
B.5 Filter Optimization 150
B.6 Time to Collision 150
C Patent Investigation 151
D Publications, Patents and Awards 153
Bibliography 155
Index 165
|
| adam_txt |
1 Introduction 1
2 State of the Art 5
2.1 Pedestrian Detection Systems 5
2.1.1 Market Aspects 5
2.1.2 Vision Based Systems 6
2.1.3 Infrared Camera Systems 8
2.1.4 Systems Based on Laserscanners 10
2.1.5 Radar Systems 11
2.1.6 Pyroelectric Sensor Systems 12
2.1.7 Pedestrian Detection with Thermopiles 13
2.1.8 Multiple Sensor Systems 14
2.1.9 Collision Assessment 15
2.2 Pedestrian Protecrion Related Issues 16
2.2.1 Legal Regulations 16
2.2.2 Accident Statistics 17
2.3 Discussion 18
3 Sensor and System Description 20
3.1 System Setup 20
3.2 Thermopiles 21
3.2.1 Detector Parameters 24
3.3 Radar Sensor 25
3.3.1 Characteristics 25
3.3.2 Localization 27
3.3.3 SpecificationoftheUtilized Sensors 29
3.4 Data Communication 29
4 Physical Fundamentals of Infrared Detection 32
4.1 Infrared Radiation 32
4.2 Radiometry 33
4.3 Atmospheric Transmission 37
4.3.1 Absorption 38
4.3.2 Scattering 38
4.4 Principles of Infrared Detection 40
5 Thermopile Pedestrian Detection System 42
5.1 Thermopile System Design 42
5.2 Sensor Arrangement for 2 D Position Estimation 43
5.2.1 Object Localization 44
5.2.2 Sensor Arrangement Requirements 45
5.2.3 Positioning Parameters 46
5.2.4 Complexity of the Sensor Arrangement 47
5.2.5 Grid Based Optimization 48
5.2.6 Simulated Annealing 50
5.2.7 Objective function 52
5.2.8 Results 55
5.3 Sensor Arrangement Calibration 56
5.3.1 Calibration Procedure 56
5.3.2 Position and Alignment Computation 58
5.4 Probabilistic Signal Processing Methods 59
5.4.1 Preprocessing of the Thermopile Signals 60
5.4.2 Thermopile Signal Interpretation 61
5.4.3 Probability Fusion 69
5.5 Position estimation with Occupancy Grid 73
5.5.1 Occupancy Grid Method 73
5.5.2 Grid Update 75
5.6 Segmentation 80
5.7 Benefit of Incorporating Radar Sensors into the System 83
5.7.1 Classification 83
6 Thermopile and Radar Sensor Data Fusion 86
6.1 Sensor Fusion Architectures 87
6.1.1 Architectures in Comparison 89
6.1.2 Thermopile and Radar Sensor Fusion Architecture 90
6.2 Multiple Target, Multiple Sensor Tracking 93
6.2.1 Overview of the Tracking Process 93
6.2.2 Kaiman Filtering and Prediction 95
6.2.3 Data Association 99
6.2.4 Sensor Target Fusion 101
6.2.5 Ego morJon Compensation 102
6.3 Fusion of Classification Results 105
6.3.1 Object Types 105
6.3.2 Dempster ShaferTheory(DST) 107
6.3.3 Comparison ofBayesian and Dempster Shafer Fusion Techniques . 111
6.3.4 Implementation of the Object Type Fusion 114
7 Collision Assessment 119
7.1 Situation Analysis Trigger Algorithm 119
7.1.1 Dimension of the Triggering Region in Longitudinal Direction . 120
7.1.2 Sizeofthe Triggering Region in Lateral Direction 122
7.2 Crash Relevant Target Filter and Decision Algorithm 123
7.2.1 Temporal Position Reconstruction of the Pedestrian 124
7.2.2 Tempora] Reconstruction of the Thermopile Signal 124
7.2.3 Comparison of the Theoretical and Actual Thermopile Signals . 127
8 Tests and Results 129
8.1 Statistical Evaluation of Classifiers 129
8.2 Generation of the Measurement Data Base 132
8.3 Quantitative System Analysis 133
8.4 Qualitative System Analysis 139
9 Conclusions 141
A Notation 143
B Calculations and Proofs 147
B.l Bayesian Inference 147
B.2 SimilarityofBayesandDST 147
B.3 Implementation of the SWF 148
B.4 Process and Measurement Noise Matrix 149
B.5 Filter Optimization 150
B.6 Time to Collision 150
C Patent Investigation 151
D Publications, Patents and Awards 153
Bibliography 155
Index 165 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Linzmeier, Dirk |
| author_facet | Linzmeier, Dirk |
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| author_sort | Linzmeier, Dirk |
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| discipline | Verkehr / Transport |
| discipline_str_mv | Verkehr / Transport |
| edition | Als Ms. gedr. |
| format | Thesis Book |
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| genre_facet | Hochschulschrift |
| id | DE-604.BV021797348 |
| illustrated | Illustrated |
| index_date | 2024-07-02T15:46:39Z |
| indexdate | 2025-02-20T06:41:48Z |
| institution | BVB |
| isbn | 3183628120 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-015009915 |
| oclc_num | 500238161 |
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| owner_facet | DE-91G DE-BY-TUM DE-210 DE-83 DE-862 DE-BY-FWS |
| physical | VIII, 166 S. Ill., graph. Darst. |
| publishDate | 2006 |
| publishDateSearch | 2006 |
| publishDateSort | 2006 |
| publisher | VDI-Verl. |
| record_format | marc |
| series | Fortschritt-Berichte VDI |
| series2 | Fortschritt-Berichte VDI : Reihe 12, Verkehrstechnik/Fahrzeugtechnik |
| spellingShingle | Linzmeier, Dirk Real-time detection of pedestrians from a moving vehicle using thermophile and radar sensor fusion Fortschritt-Berichte VDI Sensor-Array (DE-588)4213726-3 gnd Objekterkennung (DE-588)4314334-9 gnd Fußgänger (DE-588)4140907-3 gnd Radarsensor (DE-588)4809985-5 gnd Infrarotdetektor (DE-588)4161692-3 gnd Straßenfahrzeug (DE-588)4137755-2 gnd |
| subject_GND | (DE-588)4213726-3 (DE-588)4314334-9 (DE-588)4140907-3 (DE-588)4809985-5 (DE-588)4161692-3 (DE-588)4137755-2 (DE-588)4113937-9 |
| title | Real-time detection of pedestrians from a moving vehicle using thermophile and radar sensor fusion |
| title_auth | Real-time detection of pedestrians from a moving vehicle using thermophile and radar sensor fusion |
| title_exact_search | Real-time detection of pedestrians from a moving vehicle using thermophile and radar sensor fusion |
| title_exact_search_txtP | Real-time detection of pedestrians from a moving vehicle using thermophile and radar sensor fusion |
| title_full | Real-time detection of pedestrians from a moving vehicle using thermophile and radar sensor fusion Dirk Linzmeier |
| title_fullStr | Real-time detection of pedestrians from a moving vehicle using thermophile and radar sensor fusion Dirk Linzmeier |
| title_full_unstemmed | Real-time detection of pedestrians from a moving vehicle using thermophile and radar sensor fusion Dirk Linzmeier |
| title_short | Real-time detection of pedestrians from a moving vehicle using thermophile and radar sensor fusion |
| title_sort | real time detection of pedestrians from a moving vehicle using thermophile and radar sensor fusion |
| topic | Sensor-Array (DE-588)4213726-3 gnd Objekterkennung (DE-588)4314334-9 gnd Fußgänger (DE-588)4140907-3 gnd Radarsensor (DE-588)4809985-5 gnd Infrarotdetektor (DE-588)4161692-3 gnd Straßenfahrzeug (DE-588)4137755-2 gnd |
| topic_facet | Sensor-Array Objekterkennung Fußgänger Radarsensor Infrarotdetektor Straßenfahrzeug Hochschulschrift |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015009915&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV000761054 |
| work_keys_str_mv | AT linzmeierdirk realtimedetectionofpedestriansfromamovingvehicleusingthermophileandradarsensorfusion |
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