Download or read book Visual Odometry Using Line Features and Machine Learning Enhanced Line Description written by Manuel Lange and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Visual Odometry Using Line Features and Machine Learning Enhanced Line Description written by Manuel Lange and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The research on 2D lines in images has increased strongly in the last decade; on the one hand, due to more computing power available, on the other hand, due to an increased interest in odometry methods and autonomous systems. Line features have some advantages over the more thoroughly researched point features. Lines are detected on gradients, they do not need texture to be found. Thus, as long as there are gradients between homogeneous regions, they can cope with difficult situations in which mostly homogeneous areas are present. By being detected on gradients, they are also well suited to represent structure. Furthermore, lines have a very high accuracy orthogonal to their direction, as they consist of numerous points which all lie on the gradient contributing to this locational accuracy. First, we introduce a visual odometry approach which achieves real-time performance and runs solely using lines features, it does not require point features. We developed a heuristic filter algorithm which takes neighbouring line features into account and thereby improves tracking of lines and matching of lines in images taken from arbitrary camera locations. This increases the number of tracked lines and is especially beneficial in difficult scenes where it is hard to match lines by tracking them. Additionally, we employed the Cayley representation for 3D lines to avoid overparameterization in the optimization. To show the advancement of the method, it is benchmarked on commonly used datasets and compared to other state of the art approaches. Second, we developed a machine learning based line feature descriptor for line matching. This descriptor can be used to match lines from arbitrary camera locations. The training data was created synthetically using the Unreal Engine 4. We trained a model based on the ResNet architecture using a triplet loss. We evaluated the descriptor on real world scenes and show its improvement over the famous Line Band Descriptor. Third, we build upon our previous descriptor to create an improved version. Therefor, we added an image pyramid, gabor wavelets and increased the descriptor size. The evaluation of the new descriptor additionally contains competing new approaches which are also machine learning based. It shows that our improved approach outperforms them. Finally, we provide an extended evaluation of our descriptor which shows the influences of different settings and processing steps. And we present an analysis of settings for practical usage scenarios. The influence of a maximum descriptor distance threshold, of a Left-Right consistency check and of a descriptor distance ratio threshold between the first and second best match were investigated. It turns out that, for the ratio of true to false matches, it is almost always better to use a descriptor distance ratio threshold than a maximum descriptor distance threshold.
Download or read book Analysis of Geometry and Deep Learning based Methods for Visual Odometry written by You-Yi Jau and published by . This book was released on 2020 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the fields of VR, AR, and autonomous driving, it is critical to track the accurate location of an agent using cameras. This thesis dives into the problem of using ordered image sequences for localization, known as visual odometry. The lines of research can be categorized into two main group, geometry-based methods and deep learning-based methods. Geometry-based methods have been explored for over a decade, which yield robust real-time prediction in both outdoor and indoor environments. In recent years, deep learning-based methods show the potential to outperform geometry-based methods in localization. However, they are yet to be proved as accurate in variety of scenes. In this thesis, we first dive into a complete geometry-based pipeline and point out the key factors for a robust system. Second, we design a deep learning-based camera pose estimation pipeline with geometric constraints, which generalizes better than the learning-based baselines under two datasets. In the end, we explore the possibility of enhancing deep learning prediction based on geometric optimization. The thesis plots a road for combining both methods by thorough comparison. By leveraging the advantages of geometry-based and learning-based methods, the future of a robust visual odometry system can be anticipated.
Download or read book Visual Sensors written by Oscar Reinoso and published by MDPI. This book was released on 2020-03-27 with total page 738 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visual sensors are able to capture a large quantity of information from the environment around them. A wide variety of visual systems can be found, from the classical monocular systems to omnidirectional, RGB-D, and more sophisticated 3D systems. Every configuration presents some specific characteristics that make them useful for solving different problems. Their range of applications is wide and varied, including robotics, industry, agriculture, quality control, visual inspection, surveillance, autonomous driving, and navigation aid systems. In this book, several problems that employ visual sensors are presented. Among them, we highlight visual SLAM, image retrieval, manipulation, calibration, object recognition, navigation, etc.
Download or read book Deep Learning for Marine Science written by Haiyong Zheng and published by Frontiers Media SA. This book was released on 2024-05-15 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning (DL), mainly composed of deep and complex neural networks such as recurrent network and convolutional network, is an emerging research branch in the field of artificial intelligence and machine learning. DL revolution has a far-reaching impact on all scientific disciplines and every corner of our lives. With continuing technological advances, marine science is entering into the big data era with the exponential growth of information. DL is an effective means of harnessing the power of big data. Combined with unprecedented data from cameras, acoustic recorders, satellite remote sensing, and large model outputs, DL enables scientists to solve complex problems in biology, ecosystems, climate, energy, as well as physical and chemical interactions. Although DL has made great strides, it is still only beginning to emerge in many fields of marine science, especially towards representative applications and best practices for the automatic analysis of marine organisms and marine environments. DL in nowadays' marine science mainly leverages cutting-edge techniques of deep neural networks and massive data which collected by in-situ optical or acoustic imaging sensors for underwater applications, such as plankton classification and coral reef detection. This research topic aims to expand the applications of marine science to cover all aspects of detection, classification, segmentation, localization, and density estimation of marine objects, organisms, and phenomena.
Download or read book Multimodal Scene Understanding written by Michael Yang and published by Academic Press. This book was released on 2019-07-16 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms. Researchers collecting and analyzing multi-sensory data collections – for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful. Contains state-of-the-art developments on multi-modal computing Shines a focus on algorithms and applications Presents novel deep learning topics on multi-sensor fusion and multi-modal deep learning
Download or read book Computer Vision ECCV 2022 written by Shai Avidan and published by Springer Nature. This book was released on 2022-10-22 with total page 828 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Download or read book Advances in Guidance Navigation and Control written by Liang Yan and published by Springer Nature. This book was released on 2023-02-10 with total page 7455 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features the latest theoretical results and techniques in the field of guidance, navigation, and control (GNC) of vehicles and aircrafts. It covers a wide range of topics, including but not limited to, intelligent computing communication and control; new methods of navigation, estimation and tracking; control of multiple moving objects; manned and autonomous unmanned systems; guidance, navigation and control of miniature aircraft; and sensor systems for guidance, navigation and control etc. Presenting recent advances in the form of illustrations, tables, and text, it also provides detailed information of a number of the studies, to offer readers insights for their own research. In addition, the book addresses fundamental concepts and studies in the development of GNC, making it a valuable resource for both beginners and researchers wanting to further their understanding of guidance, navigation, and control.
Download or read book Neurorobotics explores machine learning written by Fei Chen and published by Frontiers Media SA. This book was released on 2023-01-20 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Autonomous Driving Perception written by Rui Fan and published by Springer Nature. This book was released on 2023-10-06 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the captivating world of computer vision and deep learning for autonomous driving with our comprehensive and in-depth guide. Immerse yourself in an in-depth exploration of cutting-edge topics, carefully crafted to engage tertiary students and ignite the curiosity of researchers and professionals in the field. From fundamental principles to practical applications, this comprehensive guide offers a gentle introduction, expert evaluations of state-of-the-art methods, and inspiring research directions. With a broad range of topics covered, it is also an invaluable resource for university programs offering computer vision and deep learning courses. This book provides clear and simplified algorithm descriptions, making it easy for beginners to understand the complex concepts. We also include carefully selected problems and examples to help reinforce your learning. Don't miss out on this essential guide to computer vision and deep learning for autonomous driving.
Download or read book Proceedings of the 13th International Conference on Computer Engineering and Networks written by Yonghong Zhang and published by Springer Nature. This book was released on 2024-01-03 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to examine innovation in the fields of computer engineering and networking. The text covers important developments in areas such as artificial intelligence, machine learning, information analysis, communication system, computer modeling, internet of things. This book presents papers from the 13th International Conference on Computer Engineering and Networks (CENet2023) held in Wuxi, China on November 3-5, 2023.
Download or read book Artificial Intelligence written by Lu Fang and published by Springer Nature. This book was released on 2022-01-01 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 13069-13070 constitutes selected papers presented at the First CAAI International Conference on Artificial Intelligence, held in Hangzhou, China, in June 2021. Due to the COVID-19 pandemic the conference was partially held online. The 105 papers were thoroughly reviewed and selected from 307 qualified submissions. The papers are organized in topical sections on applications of AI; computer vision; data mining; explainability, understandability, and verifiability of AI; machine learning; natural language processing; robotics; and other AI related topics.
Download or read book Signal and Information Processing Networking and Computers written by Yue Wang and published by Springer Nature. This book was released on with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Intelligent Robotics and Applications written by Chee Seng Chan and published by Springer. This book was released on 2021-01-09 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 13th International Conference on Intelligent Robotics and Applications, ICIRA 2020, held in Kuala Lumpur, Malaysia, in November 2020. The 45 full papers and 3 short papers were carefully reviewed and selected from 66 submissions. The accepted papers were grouped into various subtopics including Advanced Measurement and Machine Vision System; Automation; Human-Robot Interaction; Mobile Robots and Intelligent Autonomous System; Recent Trends in Computational Intelligence; Robot Design, and Development and Control. Due to the Corona pandemic ICIRA 2020 was held as a virtual event.
Download or read book Robotics Vision and Control written by Peter Corke and published by Springer Nature. This book was released on 2023-05-09 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive, but tutorial, introduction to robotics, computer vision, and control. It is written in a light but informative conversational style, weaving text, figures, mathematics, and lines of code into a narrative that covers robotics and computer vision—separately, and together as robotic vision. Over 1600 code examples show how complex problems can be decomposed and solved using just a few simple lines of code. This edition is based on Python and is accompanied by fully open-source Python-based Toolboxes for robotics and machine vision. The new Toolboxes enable the reader to easily bring the algorithmic concepts into practice and work with real, non-trivial, problems on a broad range of computing platforms. For the beginning student the book makes the algorithms accessible, the Toolbox code can be read to gain understanding, and the examples illustrate how it can be used. The code can also be the starting point for new work, for practitioners, students, or researchers, by writing programs based on Toolbox functions, or modifying the Toolbox code itself.
Download or read book Cognitive Computing for Human Robot Interaction written by Mamta Mittal and published by Academic Press. This book was released on 2021-08-13 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cognitive Computing for Human-Robot Interaction: Principles and Practices explores the efforts that should ultimately enable society to take advantage of the often-heralded potential of robots to provide economical and sustainable computing applications. This book discusses each of these applications, presents working implementations, and combines coherent and original deliberative architecture for human–robot interactions (HRI). Supported by experimental results, it shows how explicit knowledge management promises to be instrumental in building richer and more natural HRI, by pushing for pervasive, human-level semantics within the robot's deliberative system for sustainable computing applications. This book will be of special interest to academics, postgraduate students, and researchers working in the area of artificial intelligence and machine learning. Key features: Introduces several new contributions to the representation and management of humans in autonomous robotic systems; Explores the potential of cognitive computing, robots, and HRI to generate a deeper understanding and to provide a better contribution from robots to society; Engages with the potential repercussions of cognitive computing and HRI in the real world. Introduces several new contributions to the representation and management of humans in an autonomous robotic system Explores cognitive computing, robots and HRI, presenting a more in-depth understanding to make robots better for society Gives a challenging approach to those several repercussions of cognitive computing and HRI in the actual global scenario
Download or read book Machine Learning for Cyber Security written by Yuan Xu and published by Springer Nature. This book was released on 2023-01-12 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume proceedings set LNCS 13655,13656 and 13657 constitutes the refereedproceedings of the 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, which taking place during December 2–4, 2022, held in Guangzhou, China. The 100 full papers and 46 short papers were included in these proceedings were carefully reviewed and selected from 367 submissions.
