Stereo Vision Based Road Condition Monitoring
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Stereo Vision Based Road Condition Monitoring
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Author : Brunken, Hauke
language : en
Publisher: Universitätsverlag der TU Berlin
Release Date : 2021-05-12
Stereo Vision Based Road Condition Monitoring written by Brunken, Hauke and has been published by Universitätsverlag der TU Berlin this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-12 with Technology & Engineering categories.
When planning road construction measures, it is essential to have up-to-date information on road conditions. If this information is not to be obtained manually, it is currently obtained using laser scanners mounted on mobile mapping vehicles, which can measure the 3D road profile. However, a large number of mobile mapping vehicles would be necessary to record an entire road network on a regular basis. Since 2D road damages can be found automatically on monocular camera images, the idea was born to use a stereo camera system to capture the 3D profile of roads. With stereo camera systems, it would be possible to equip a large number of vehicles and regularly collect data from large road networks. In this thesis, the potential applications of a stereo camera system for measuring road profiles, which is mounted behind the windshield of a vehicle, are investigated. Since this requires a calibration of the stereo camera system, but the effort for the user should be kept low, the camera self-calibration for this application is also examined. 3D reconstruction from stereoscopic images is a well-studied topic, but its application on road surfaces with little and repetitive textures requires special algorithms. For this reason, a new stereo method was developed. It is based on the plane-sweep approach in combination with semi-global matching. It was tested with different measures for pixel comparison. Furthermore, the plane-sweep approach was implemented in a neural network that solves the stereo correspondence problem in a single step. It uses the stereoscopic images as input and provides an elevation image as output. A completely new approach was developed for the self-calibration of mono cameras and stereo camera systems. Previous methods search for feature points in several images of the same scene. The points are matched between the images and used for the calibration. In contrast to these methods, the proposed method uses feature maps instead of feature points to compare multiple views of one and the same plane. To estimate the unknown parameters, the backpropagation algorithm is used together with the gradient descent method. The measurements obtained by stereoscopic image processing were compared with those obtained by industrial laser scanners. They show that both measurements are very close to each other and that a stereoscopic camera system is in principle suitable for capturing the surface profile of a road. Experiments show that the proposed self-calibration method is capable of estimating all parameters of a complex camera model, including lens distortion, with high precision. Bei der Planung von Straßenbaumaßnahmen ist es unabdingbar, über aktuelle Informationen über den Straßenzustand zu verfügen. Sollen diese Informationen nicht manuell gewonnen werden, werden derzeit Messfahrzeug mit Laserscannern verwendet, welche das 3D-Straßenprofil vermessen können. Für die regelmäßige Erfassung eines gesamten Straßennetzes wäre jedoch eine große Anzahl von Messfahrzeugen erforderlich. Da 2D-Straßenschäden automatisch auf monokularen Kamerabildern gefunden werden können, entstand die Idee, ein Stereokamerasystem zur Erfassung des 3D-Profils zu verwenden. Eine große Anzahl von Fahrzeugen könnte damit ausgerüstet werden und es könnten regelmäßig Daten von großen Straßennetzen erfasst werden. In dieser Arbeit werden die Einsatzmöglichkeiten eines Stereokamerasystems zur Messung von Straßenprofilen untersucht, dass sich hinter der Windschutzscheibe eines Fahrzeugs befindet. Da hierzu das Stereokamerasystems kalibriert sein muss, der Aufwand für den Anwender aber geringgehalten werden soll, wird außerdem die Selbstkalibrierung für diesen Einsatzzweck untersucht. Die 3D-Rekonstruktion aus stereoskopischen Bildern ist ein viel untersuchtes Thema, aber ihre Anwendung auf Straßenoberflächen mit wenig und sich wiederholenden Texturen erfordert spezielle Algorithmen. Aus diesem Grund wurde ein neues Stereoverfahren entwickelt. Es basiert auf dem Plane-sweep-Ansatz in Kombination mit Semi-global Matching. Es wurde mit verschiedene Maßen für den Vergleich von Pixeln getestet. Darüber hinaus wurde der Plane-sweep-Ansatz in einem neuronalen Netzwerk implementiert, das das Stereo-Korrespondenzproblem in einem einzigen Schritt löst. Es verwendet die stereoskopischen Bilder als Eingabe und liefert als Ausgabe ein Höhenbild. Für die Selbstkalibrierung von Monokameras und Stereokamerasystemen wurde ein völlig neuer Ansatz entwickelt. Bisherige Methoden suchen nach Merkmalspunkten in mehreren Bildern der gleichen Szene. Die Punkte werden zwischen den Bildern zugeordnet und für die Kalibrierung verwendet. Die vorgeschlagene Methode verwendet anstelle von Merkmalspunkten Feature-Maps um mehrere Ansichten derselben Ebene zu vergleichen. Zur Schätzung der unbekannten Parameter wird der Backpropagation-Algorithmus zusammen mit dem Gradientenabstiegsverfahren verwendet. Die durch stereoskopische Bildverarbeitung erhaltenen Messungen wurden mit Messungen von industriellen Laserscannern verglichen. Sie zeigen, dass beide sehr nahe beieinander liegen und dass ein Stereokamerasystem für die Erfassung des Oberflächenprofils einer Straße grundsätzlich geeignet ist. Experimente zeigen, dass die neue Selbstkalibrierungsmethode in der Lage ist, alle Parameter eines komplexen Kameramodells, einschließlich der Linsenverzerrung, mit hoher Präzision abzuschätzen.
Stereo Vision Based Road Condition Monitoring
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Author : Hauke Brunken
language : en
Publisher:
Release Date : 2021
Stereo Vision Based Road Condition Monitoring written by Hauke Brunken and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Road Condition Estimation With Data Mining Methods Using Vehicle Based Sensors
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Author : Masino, Johannes
language : en
Publisher: KIT Scientific Publishing
Release Date : 2021-03-31
Road Condition Estimation With Data Mining Methods Using Vehicle Based Sensors written by Masino, Johannes and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-31 with Technology & Engineering categories.
The work provides novel methods to process inertial sensor and acoustic sensor data for road condition estimation and monitoring with application in vehicles, which serve as sensor platforms. Furthermore, methods are introduced to combine the results from various vehicles for a more reliable estimation.
Computer Vision And Imaging In Intelligent Transportation Systems
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Author : Robert P. Loce
language : en
Publisher: John Wiley & Sons
Release Date : 2017-03-20
Computer Vision And Imaging In Intelligent Transportation Systems written by Robert P. Loce and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-20 with Technology & Engineering categories.
Acts as single source reference providing readers with an overview of how computer vision can contribute to the different applications in the field of road transportation This book presents a survey of computer vision techniques related to three key broad problems in the roadway transportation domain: safety, efficiency, and law enforcement. The individual chapters present significant applications within those problem domains, each presented in a tutorial manner, describing the motivation for and benefits of the application, and a description of the state of the art. Key features: Surveys the applications of computer vision techniques to road transportation system for the purposes of improving safety and efficiency and to assist law enforcement. Offers a timely discussion as computer vision is reaching a point of being useful in the field of transportation systems. Available as an enhanced eBook with video demonstrations to further explain the concepts discussed in the book, as well as links to publically available software and data sets for testing and algorithm development. The book will benefit the many researchers, engineers and practitioners of computer vision, digital imaging, automotive and civil engineering working in intelligent transportation systems. Given the breadth of topics covered, the text will present the reader with new and yet unconceived possibilities for application within their communities.
Optimization Of Adaptive Test Design Methods For The Determination Of Steady State Data Driven Models In Terms Of Combustion Engine Calibration
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Author : Sandmeier, Nino
language : en
Publisher: Universitätsverlag der TU Berlin
Release Date : 2022-12-01
Optimization Of Adaptive Test Design Methods For The Determination Of Steady State Data Driven Models In Terms Of Combustion Engine Calibration written by Sandmeier, Nino and has been published by Universitätsverlag der TU Berlin this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-01 with Technology & Engineering categories.
This thesis deals with the development of a model-based adaptive test design strategy with a focus on steady-state combustion engine calibration. The first research topic investigates the question how to handle limits in the input domain during an adaptive test design procedure. The second area of scope aims at identifying the test design method providing the best model quality improvement in terms of overall model prediction error. To consider restricted areas in the input domain, a convex hull-based solution involving a convex cone algorithm is developed, the outcome of which serves as a boundary model for a test point search. A solution is derived to enable the application of the boundary model to high-dimensional problems without calculating the exact convex hull and cones. Furthermore, different data-driven engine modeling methods are compared, resulting in the Gaussian process model as the most suitable one for a model-based calibration. To determine an appropriate test design method for a Gaussian process model application, two new strategies are developed and compared to state-of-the-art methods. A simulation-based study shows the most benefit applying a modified mutual information test design, followed by a newly developed relevance-based test design with less computational effort. The boundary model and the relevance-based test design are integrated into a multicriterial test design strategy that is tailored to match the requirements of combustion engine test bench measurements. A simulation-based study with seven and nine input parameters and four outputs each offered an average model quality improvement of 36 % and an average measured input area volume increase of 65 % compared to a non-adaptive space-filling test design. The multicriterial test design was applied to a test bench measurement with seven inputs for verification. Compared to a space-filling test design measurement, the improvement could be confirmed with an average model quality increase of 17 % over eight outputs and a 34 % larger measured input area. Diese Arbeit befasst sich mit der Entwicklung einer modellbasierten adaptiven Versuchsplanungsstrategie für die Anwendung in der Applikation des Stationärverhaltens von Verbrennungsmotoren. Der erste Forschungsteil untersucht, wie sich Grenzen im Eingangsraum in die Versuchsplanung eines adaptiven Prozesses einbinden lassen. Ein weiterer Fokus liegt auf der Identifikation einer modellbasierten Versuchsplanung, die eine bestmögliche Verbesserung der globalen Modellqualität hinsichtlich des Prädiktionsfehlers ermöglicht. Es wird ein Grenzraummodell auf Basis der konvexen Hülle unter Zuhilfenahme eines Algorithmus zur Bestimmung eines konvexen Konus entwickelt, das als Grundlage für eine Versuchsplanung in beschränkten Eingangsräumen verwendet wird. Um die Anwendbarkeit bei hochdimensionalen Problemstellungen zu gewährleisten, wird ein Verfahren vorgestellt, das eine Berechnung auch ohne die Bestimmung der exakten konvexen Hülle und konvexen Konen ermöglicht. Des Weiteren werden verschiedene Methoden zur datengetriebenen Modellbildung des Verbrennungsmotors verglichen, wobei das Gauß-Prozess Modell als die geeignetste Modellierungsmethode hervorgeht. Um die bestmögliche Versuchsplanungsmethode bei der Anwendung des Gauß-Prozess Modells zu ermitteln, werden zwei neue Strategien entwickelt und mit verfügbaren Methoden aus der Literatur verglichen. Eine simulationsbasierte Studie zeigt, dass eine angepasste Mutual Information Methode die besten Ergebnisse liefert. Ein neu entwickeltes relevanzbasiertes Verfahren erreicht die zweitbesten Ergebnisse, bietet aber einen geringeren Berechnungsaufwand als das Mutual Information Verfahren. Das Grenzmodell und das relevanzbasierte Verfahren werden in einem multikriteriellen Versuchsplanungsverfahren zusammengeführt, das an die Anforderungen von Messungen an einem Verbrennungsmotorenprüfstand angepasst ist. In einer simulationsbasierten Studie mit sieben bzw. neun Eingangsparametern und jeweils vier Ausgängen konnte eine durchschnittliche Modellqualitätsverbesserung von 36 % und eine mittlere Vergrößerung des vermessenen Eingangsraumvolumens von 65 % im Vergleich zu einer nichtadaptiven raumfüllenden Versuchsplanung gezeigt werden. Das multikriterielle Versuchsplanungsverfahren wurde anhand von Prüfstandsmessungen mit sieben Eingangsparametern verifiziert. Im Vergleich zu einer raumfüllenden Versuchsplanung konnte eine mittlere Modellqualitätsverbesserung über alle acht Ausgänge von 17 % und ein um 34 % vergrößertes vermessenes Eingangsraumvolumen erreicht werden, wodurch die Ergebnisse der Simulationen bestätigt werden konnten.
Data Driven Methods For Civil Structural Health Monitoring And Resilience
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Author : Mohammad Noori
language : en
Publisher: CRC Press
Release Date : 2023-10-26
Data Driven Methods For Civil Structural Health Monitoring And Resilience written by Mohammad Noori and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-26 with Technology & Engineering categories.
Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides a comprehensive overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This allows existing structures to be turned into smart structures, thereby allowing them to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis. Artificial-intelligence-based methodologies are becoming increasingly more attractive for civil engineering and SHM applications; machine learning and deep learning methods can be applied and further developed to transform the available data into valuable information for engineers and decision makers.
Computer Vision Eccv 2016 Workshops
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Author : Gang Hua
language : en
Publisher: Springer
Release Date : 2016-09-17
Computer Vision Eccv 2016 Workshops written by Gang Hua and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-17 with Computers categories.
The three-volume set LNCS 9913, LNCS 9914, and LNCS 9915 comprises the refereed proceedings of the Workshops that took place in conjunction with the 14th European Conference on Computer Vision, ECCV 2016, held in Amsterdam, The Netherlands, in October 2016. 27 workshops from 44 workshops proposals were selected for inclusion in the proceedings. These address the following themes: Datasets and Performance Analysis in Early Vision; Visual Analysis of Sketches; Biological and Artificial Vision; Brave New Ideas for Motion Representations; Joint Imagenet and MS Coco Visual Recognition Challenge; Geometry Meets Deep Learning; Action and Anticipation for Visual Learning; Computer Vision for Road Scene Understanding and Autonomous Driving; Challenge on Automatic Personality Analysis; BioImage Computing; Benchmarking Multi-Target Tracking: MOTChallenge; Assistive Computer Vision and Robotics; Transferring and Adapting Source Knowledge in Computer Vision; Recovering 6D Object Pose; Robust Reading; 3D Face Alignment in the Wild and Challenge; Egocentric Perception, Interaction and Computing; Local Features: State of the Art, Open Problems and Performance Evaluation; Crowd Understanding; Video Segmentation; The Visual Object Tracking Challenge Workshop; Web-scale Vision and Social Media; Computer Vision for Audio-visual Media; Computer VISion for ART Analysis; Virtual/Augmented Reality for Visual Artificial Intelligence; Joint Workshop on Storytelling with Images and Videos and Large Scale Movie Description and Understanding Challenge.
Computer Vision For Driver Assistance
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Author : Mahdi Rezaei
language : en
Publisher: Springer
Release Date : 2017-02-06
Computer Vision For Driver Assistance written by Mahdi Rezaei and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-06 with Mathematics categories.
This book summarises the state of the art in computer vision-based driver and road monitoring, focussing on monocular vision technology in particular, with the aim to address challenges of driver assistance and autonomous driving systems. While the systems designed for the assistance of drivers of on-road vehicles are currently converging to the design of autonomous vehicles, the research presented here focuses on scenarios where a driver is still assumed to pay attention to the traffic while operating a partially automated vehicle. Proposing various computer vision algorithms, techniques and methodologies, the authors also provide a general review of computer vision technologies that are relevant for driver assistance and fully autonomous vehicles. Computer Vision for Driver Assistance is the first book of its kind and will appeal to undergraduate and graduate students, researchers, engineers and those generally interested in computer vision-related topics in modern vehicle design.
Pattern Recognition
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Author : Juergen Gall
language : en
Publisher: Springer
Release Date : 2015-10-06
Pattern Recognition written by Juergen Gall and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-06 with Computers categories.
This book constitutes the refereed proceedings of the 37th German Conference on Pattern Recognition, GCPR 2015, held in Aachen, Germany, in October 2015. The 45 revised full papers and one Young Researchers Forum presented were carefully reviewed and selected from 108 submissions. The papers are organized in topical sections on motion and reconstruction; mathematical foundations and image processing; biomedical image analysis and applications; human pose analysis; recognition and scene understanding.
Frontiers Of Computer Vision
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Author : Hieyong Jeong
language : en
Publisher: Springer Nature
Release Date : 2021-07-14
Frontiers Of Computer Vision written by Hieyong Jeong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-14 with Computers categories.
This book constitutes refereed proceedings of the 27th International Workshop Frontiers of Computer Vision, IW-FCV 2021, held in Daegu, South Korea, in February 2021. The 17 full papers and 8 short papers presented were thoroughly reviewed and selected from 44 submissions. The papers in the volume are organized according to the following topics: real-world applications; segmentation / object tracking; recognition; human behaviour; algorithm / application.