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 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 Algorithmic Advances in Riemannian Geometry and Applications written by Hà Quang Minh and published by Springer. This book was released on 2016-10-05 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a selection of the most recent algorithmic advances in Riemannian geometry in the context of machine learning, statistics, optimization, computer vision, and related fields. The unifying theme of the different chapters in the book is the exploitation of the geometry of data using the mathematical machinery of Riemannian geometry. As demonstrated by all the chapters in the book, when the data is intrinsically non-Euclidean, the utilization of this geometrical information can lead to better algorithms that can capture more accurately the structures inherent in the data, leading ultimately to better empirical performance. This book is not intended to be an encyclopedic compilation of the applications of Riemannian geometry. Instead, it focuses on several important research directions that are currently actively pursued by researchers in the field. These include statistical modeling and analysis on manifolds,optimization on manifolds, Riemannian manifolds and kernel methods, and dictionary learning and sparse coding on manifolds. Examples of applications include novel algorithms for Monte Carlo sampling and Gaussian Mixture Model fitting, 3D brain image analysis,image classification, action recognition, and motion tracking.

Download or read book The Proceedings of the 2021 Asia Pacific International Symposium on Aerospace Technology APISAT 2021 Volume 2 written by Sangchul Lee and published by Springer Nature. This book was released on 2022-09-29 with total page 1396 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceeding comprises peer-reviewed papers of the 2021 Asia-Pacific International Symposium on Aerospace Technology (APISAT 2021), held from 15-17 November 2021 in Jeju, South Korea. This book deals with various themes on computational fluid dynamics, wind tunnel testing, flow visualization, UAV design, flight simulation, satellite attitude control, aeroelasticity and control, combustion analysis, fuel injection, cooling systems, spacecraft propulsion and so forth. So, this book can be very helpful not only for the researchers of universities and academic institutes, but also for the industry engineers who are interested in the current and future advanced topics in aerospace technology.

Download or read book Optical Flow and Deep Learning Based Approach to Visual Odometry written by Peter M. Muller and published by . This book was released on 2016 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Visual odometry is a challenging approach to simultaneous localization and mapping algorithms. Based on one or two cameras, motion is estimated from features and pixel differences from one set of frames to the next. A different but related topic to visual odometry is optical flow, which aims to calculate the exact distance and direction every pixel moves in consecutive frames of a video sequence. Because of the frame rate of the cameras, there are generally small, incremental changes between subsequent frames, in which optical flow can be assumed to be proportional to the physical distance moved by an egocentric reference, such as a camera on a vehicle. Combining these two issues, a visual odometry system using optical flow and deep learning is proposed. Optical flow images are used as input to a convolutional neural network, which calculates a rotation and displacement based on the image. The displacements and rotations are applied incrementally in sequence to construct a map of where the camera has traveled. The system is trained and tested on the KITTI visual odometry dataset, and accuracy is measured by the difference in distances between ground truth and predicted driving trajectories. Different convolutional neural network architecture configurations are tested for accuracy, and then results are compared to other state-of-the-art monocular odometry systems using the same dataset. The average translation error from this system is 10.77%, and the average rotation error is 0.0623 degrees per meter. This system also exhibits at least a 23.796x speedup over the next fastest odometry estimation system."--Abstract.

Download or read book Computer Vision ECCV 2018 Workshops written by Laura Leal-Taixé and published by Springer. This book was released on 2019-01-22 with total page 743 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six-volume set comprising the LNCS volumes 11129-11134 constitutes the refereed proceedings of the workshops that took place in conjunction with the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.43 workshops from 74 workshops proposals were selected for inclusion in the proceedings. The workshop topics present a good orchestration of new trends and traditional issues, built bridges into neighboring fields, and discuss fundamental technologies and novel applications.

Download or read book Introduction to Visual SLAM written by Xiang Gao and published by Springer Nature. This book was released on 2021-09-28 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a systematic and comprehensive introduction to the visual simultaneous localization and mapping (vSLAM) technology, which is a fundamental and essential component for many applications in robotics, wearable devices, and autonomous driving vehicles. The book starts from very basic mathematic background knowledge such as 3D rigid body geometry, the pinhole camera projection model, and nonlinear optimization techniques, before introducing readers to traditional computer vision topics like feature matching, optical flow, and bundle adjustment. The book employs a light writing style, instead of the rigorous yet dry approach that is common in academic literature. In addition, it includes a wealth of executable source code with increasing difficulty to help readers understand and use the practical techniques. The book can be used as a textbook for senior undergraduate or graduate students, or as reference material for researchers and engineers in related areas.

Download or read book ICGG 2024 Proceedings of the 21st International Conference on Geometry and Graphics written by Kazuki Takenouchi and published by Springer Nature. This book was released on with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Spectral Geometry of Shapes written by Jing Hua and published by Academic Press. This book was released on 2020-01-15 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral Geometry of Shapes presents unique shape analysis approaches based on shape spectrum in differential geometry. It provides insights on how to develop geometry-based methods for 3D shape analysis. The book is an ideal learning resource for graduate students and researchers in computer science, computer engineering and applied mathematics who have an interest in 3D shape analysis, shape motion analysis, image analysis, medical image analysis, computer vision and computer graphics. Due to the rapid advancement of 3D acquisition technologies there has been a big increase in 3D shape data that requires a variety of shape analysis methods, hence the need for this comprehensive resource. Presents the latest advances in spectral geometric processing for 3D shape analysis applications, such as shape classification, shape matching, medical imaging, etc. Provides intuitive links between fundamental geometric theories and real-world applications, thus bridging the gap between theory and practice Describes new theoretical breakthroughs in applying spectral methods for non-isometric motion analysis Gives insights for developing spectral geometry-based approaches for 3D shape analysis and deep learning of shape geometry

Download or read book Pattern Recognition and Image Analysis written by Antonio Pertusa and published by Springer Nature. This book was released on 2023-06-24 with total page 735 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2023, held in Alicante, Spain, in June 27–30, 2023. The 56 papers accepted for these proceedings were carefully reviewed and selected from 86 submissions. They deal with Machine Learning, Document Analysis, Computer Vision, 3D Computer Vision, Computer Vision Applications, Medical Imaging & Applications, Machine Learning Applications.

Download or read book RGB D Image Analysis and Processing written by Paul L. Rosin and published by Springer Nature. This book was released on 2019-10-26 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the fundamentals and recent advances in RGB-D imaging as well as covering a range of RGB-D applications. The topics covered include: data acquisition, data quality assessment, filling holes, 3D reconstruction, SLAM, multiple depth camera systems, segmentation, object detection, salience detection, pose estimation, geometric modelling, fall detection, autonomous driving, motor rehabilitation therapy, people counting and cognitive service robots. The availability of cheap RGB-D sensors has led to an explosion over the last five years in the capture and application of colour plus depth data. The addition of depth data to regular RGB images vastly increases the range of applications, and has resulted in a demand for robust and real-time processing of RGB-D data. There remain many technical challenges, and RGB-D image processing is an ongoing research area. This book covers the full state of the art, and consists of a series of chapters by internationally renowned experts in the field. Each chapter is written so as to provide a detailed overview of that topic. RGB-D Image Analysis and Processing will enable both students and professional developers alike to quickly get up to speed with contemporary techniques, and apply RGB-D imaging in their own projects.

Download or read book 3D Imaging Analysis and Applications written by Yonghuai Liu and published by Springer Nature. This book was released on 2020-09-11 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is designed for postgraduate studies in the field of 3D Computer Vision. It also provides a useful reference for industrial practitioners; for example, in the areas of 3D data capture, computer-aided geometric modelling and industrial quality assurance. This second edition is a significant upgrade of existing topics with novel findings. Additionally, it has new material covering consumer-grade RGB-D cameras, 3D morphable models, deep learning on 3D datasets, as well as new applications in the 3D digitization of cultural heritage and the 3D phenotyping of crops. Overall, the book covers three main areas: ● 3D imaging, including passive 3D imaging, active triangulation 3D imaging, active time-of-flight 3D imaging, consumer RGB-D cameras, and 3D data representation and visualisation; ● 3D shape analysis, including local descriptors, registration, matching, 3D morphable models, and deep learning on 3D datasets; and ● 3D applications, including 3D face recognition, cultural heritage and 3D phenotyping of plants. 3D computer vision is a rapidly advancing area in computer science. There are many real-world applications that demand high-performance 3D imaging and analysis and, as a result, many new techniques and commercial products have been developed. However, many challenges remain on how to analyse the captured data in a way that is sufficiently fast, robust and accurate for the application. Such challenges include metrology, semantic segmentation, classification and recognition. Thus, 3D imaging, analysis and their applications remain a highly-active research field that will continue to attract intensive attention from the research community with the ultimate goal of fully automating the 3D data capture, analysis and inference pipeline.

Download or read book RGB D Image Analysis and Processing written by Paul L. Rosin and published by Springer. This book was released on 2019-11-06 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the fundamentals and recent advances in RGB-D imaging as well as covering a range of RGB-D applications. The topics covered include: data acquisition, data quality assessment, filling holes, 3D reconstruction, SLAM, multiple depth camera systems, segmentation, object detection, salience detection, pose estimation, geometric modelling, fall detection, autonomous driving, motor rehabilitation therapy, people counting and cognitive service robots. The availability of cheap RGB-D sensors has led to an explosion over the last five years in the capture and application of colour plus depth data. The addition of depth data to regular RGB images vastly increases the range of applications, and has resulted in a demand for robust and real-time processing of RGB-D data. There remain many technical challenges, and RGB-D image processing is an ongoing research area. This book covers the full state of the art, and consists of a series of chapters by internationally renowned experts in the field. Each chapter is written so as to provide a detailed overview of that topic. RGB-D Image Analysis and Processing will enable both students and professional developers alike to quickly get up to speed with contemporary techniques, and apply RGB-D imaging in their own projects.

Download or read book Proceedings of International Conference on Recent Trends in Machine Learning IoT Smart Cities and Applications written by Vinit Kumar Gunjan and published by Springer Nature. This book was released on 2020-10-17 with total page 998 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected research papers presented at the International Conference on Recent Trends in Machine Learning, IOT, Smart Cities & Applications (ICMISC 2020), held on 29–30 March 2020 at CMR Institute of Technology, Hyderabad, Telangana, India. Discussing current trends in machine learning, Internet of things, and smart cities applications, with a focus on multi-disciplinary research in the area of artificial intelligence and cyber-physical systems, this book is a valuable resource for scientists, research scholars and PG students wanting formulate their research ideas and find the future directions in these areas. Further, it serves as a reference work anyone wishing to understand the latest technologies used by practicing engineers around the globe.

Download or read book Computer Vision written by Simon J. D. Prince and published by Cambridge University Press. This book was released on 2012-06-18 with total page 599 pages. Available in PDF, EPUB and Kindle. Book excerpt: A modern treatment focusing on learning and inference, with minimal prerequisites, real-world examples and implementable algorithms.

Download or read book Omnidirectional Vision written by Pascal Vasseur and published by John Wiley & Sons. This book was released on 2023-12-12 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Omnidirectional cameras, vision sensors that can capture 360° images, have in recent years had growing success in computer vision, robotics and the entertainment industry. In fact, modern omnidirectional cameras are compact, lightweight and inexpensive, and are thus being integrated in an increasing number of robotic platforms and consumer devices. However, the special format of output data requires tools that are appropriate for camera calibration, signal analysis and image interpretation. This book is divided into six chapters written by world-renowned scholars. In a rigorous yet accessible way, the mathematical foundation of omnidirectional vision is presented, from image geometry and camera calibration to image processing for central and non-central panoramic systems. Special emphasis is given to fisheye cameras and catadioptric systems, which combine mirrors with lenses. The main applications of omnidirectional vision, including 3D scene reconstruction and robot localization and navigation, are also surveyed. Finally, the recent trend towards AI-infused methods (deep learning architectures) and other emerging research directions are discussed.

Download or read book Advances in Machine Learning Research and Application 2012 Edition written by and published by ScholarlyEditions. This book was released on 2012-12-26 with total page 1934 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Machine Learning Research and Application / 2012 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Machine Learning. The editors have built Advances in Machine Learning Research and Application / 2012 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Machine Learning in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Advances in Machine Learning Research and Application / 2012 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.