Download or read book Image based Localization Using Feature weighted Mechanism for Adjusting Feature Correlation written by 李俊賢 and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Efficient Image Based Localization Using Machine Learning Techniques written by Ahmed Elmougi and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Localization is critical for self-awareness of any autonomous system and is an important part of the autonomous system stack which consists of many phases including sensing, perceiving, planning and control. In the sensing phase, data from on board sensors are collected, preprocessed and passed to the next phase. The perceiving phase is responsible for self awareness or localization and situational awareness which includes multi-objects detection and scene understanding. After the autonomous system is aware of where it is and what is around it, it can use this knowledge to plan for the path it can take and send control commands to pursue this path. In this proposal, we focus on the localization part of the autonomous stack using camera images. We deal with the localization problem from different perspectives including single images and videos. Starting with the single image pose estimation, our approach is to propose systems that not only have good localization accuracy, but also have low space and time complexity. Firstly, we propose SurfCNN, a low cost indoor localization system that uses SURF descriptors instead of the original images to reduce the complexity of training convolutional neural networks (CNN) for indoor localization application. Given a single input image, the strongest SURF features descriptors are used as input to 5 convolutional layers to find its absolute position and orientation in arbitrary reference frame. The proposed system achieves comparable performance to the state of the art using only 300 features without the need for using the full image or complex neural networks architectures. Following, we propose SURF-LSTM, an extension to the idea of using SURF descriptors instead the original images. However, instead of CNN used in SurfCNN, we use long short term memory (LSTM) network which is one type of recurrent neural networks (RNN) to extract the sequential relation between SURF descriptors. Using SURF-LSTM, We only need 50 features to reach comparable or better results compared with SurfCNN that needs 300 features and other works that use full images with large neural networks. In the following research phase, instead of using SURF descriptors as image features to reduce the training complexity, we study the effect of using features extracted from other CNN models that were pretrained on other image tasks like image classification without further training and fine tuning. To learn the pose from pretrained features, graph neural networks (GNN) are adopted to solve the single image localization problem (Pose-GNN) by using these features representations either as features of nodes in a graph (image as a node) or converted into a graph (image as a graph). The proposed models outperform the state of the art methods on indoor localization dataset and have comparable performance for outdoor scenes. In the final stage of single image pose estimation research, we study if we can achieve good localization results without the need for training complex neural network. We propose (Linear-PoseNet) by which we can achieve similar results to the other methods based on neural networks with training a single linear regression layer on image features from pretrained ResNet50 in less than one second on CPU. Moreover, for outdoor scenes, we propose (Dense-PoseNet) that have only 3 fully connected layers trained on few minutes that reach comparable performance to other complex methods. The second localization perspective is to find the relative poses between images in a video instead of absolute poses. We extend the idea used in SurfCNN and SURF-LSTM systems and use SURF descriptors as feature representation of the images in the video. Two systems are proposed to find the relative poses between images in the video using 3D-CNN and 2DCNN-RNN. We show that using 3D-CNN is better than using the combination of CNN-RNN for relative pose estimation.

Download or read book Computer Applications written by Min Zhang and published by Springer Nature. This book was released on 2023-12-15 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set CCIS 1959 and 1960 constitutes the refereed post-conference proceedings of the 38th CCF National Conference on Computer Applications, CCF NCCA 2023, held in Suzhou, China, during July 16–20, 2023. The 39 revised full papers presented in these proceedings were carefully reviewed and selected from 197 submissions. The papers are organized in the following topical sections: Volume I: Artificial intelligence and application. Volume II: Data science and technology; pattern recognition and machine learning; network communication and security; frontier and comprehensive applications.

Download or read book Dynamic Neural Networks for Robot Systems Data Driven and Model Based Applications written by Long Jin and published by Frontiers Media SA. This book was released on 2024-07-24 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural network control has been a research hotspot in academic fields due to the strong ability of computation. One of its wildly applied fields is robotics. In recent years, plenty of researchers have devised different types of dynamic neural network (DNN) to address complex control issues in robotics fields in reality. Redundant manipulators are no doubt indispensable devices in industrial production. There are various works on the redundancy resolution of redundant manipulators in performing a given task with the manipulator model information known. However, it becomes knotty for researchers to precisely control redundant manipulators with unknown model to complete a cyclic-motion generation CMG task, to some extent. It is worthwhile to investigate the data-driven scheme and the corresponding novel dynamic neural network (DNN), which exploits learning and control simultaneously. Therefore, it is of great significance to further research the special control features and solve challenging issues to improve control performance from several perspectives, such as accuracy, robustness, and solving speed.

Download or read book Recent Advances in Indoor Localization Systems and Technologies written by Gyula Simon and published by MDPI. This book was released on 2021-08-30 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods.

Download or read book Image and Graphics written by Yuxin Peng and published by Springer Nature. This book was released on 2021-09-30 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set LNCS 12888, 12898, and 12890 constitutes the refereed conference proceedings of the 11th International Conference on Image and Graphics, ICIG 2021, held in Haikou, China, in August 2021.* The 198 full papers presented were selected from 421 submissions and focus on advances of theory, techniques and algorithms as well as innovative technologies of image, video and graphics processing and fostering innovation, entrepreneurship, and networking. *The conference was postponed due to the COVID-19 pandemic.

Download or read book Pattern Recognition and Computer Vision written by Qingshan Liu and published by Springer Nature. This book was released on 2023-12-27 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis.

Download or read book Machine Learning in Medical Imaging written by Yinghuan Shi and published by Springer. This book was released on 2018-09-14 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 9th International Workshop on Machine Learning in Medical Imaging, MLMI 2018, held in conjunction with MICCAI 2018 in Granada, Spain, in September 2018. The 45 papers presented in this volume were carefully reviewed and selected from 82 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging.

Download or read book Artificial Intelligence and Robotics written by Huimin Lu and published by Springer Nature. This book was released on 2024-01-03 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Symposium on Artificial Intelligence and Robotics, ISAIR 2023, held in Beijing, China, during October 21–23, 2023. The 50 full papers included in this book were carefully reviewed and selected from 103 submissions. They focus on three important areas of Pattern Recognition: Artificial Intelligence; Robotics and Internet of Things, Covering Various Technical Aspects.

Download or read book Computer Vision ECCV 2018 written by Vittorio Ferrari and published by Springer. This book was released on 2018-10-06 with total page 899 pages. Available in PDF, EPUB and Kindle. Book excerpt: The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.

Download or read book Feature Extraction and Image Processing for Computer Vision written by Mark Nixon and published by Academic Press. This book was released on 2012-12-18 with total page 629 pages. Available in PDF, EPUB and Kindle. Book excerpt: Feature Extraction and Image Processing for Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in Matlab. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the exemplar code of the algorithms." Fully updated with the latest developments in feature extraction, including expanded tutorials and new techniques, this new edition contains extensive new material on Haar wavelets, Viola-Jones, bilateral filtering, SURF, PCA-SIFT, moving object detection and tracking, development of symmetry operators, LBP texture analysis, Adaboost, and a new appendix on color models. Coverage of distance measures, feature detectors, wavelets, level sets and texture tutorials has been extended. - Named a 2012 Notable Computer Book for Computing Methodologies by Computing Reviews - Essential reading for engineers and students working in this cutting-edge field - Ideal module text and background reference for courses in image processing and computer vision - The only currently available text to concentrate on feature extraction with working implementation and worked through derivation

Download or read book Towards Extensible and Adaptable Methods in Computing written by Shampa Chakraverty and published by Springer. This book was released on 2018-11-04 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses extensible and adaptable computing, a broad range of methods and techniques used to systematically tackle the future growth of systems and respond proactively and seamlessly to change. The book is divided into five main sections: Agile Software Development, Data Management, Web Intelligence, Machine Learning and Computing in Education. These sub-domains of computing work together in mutually complementary ways to build systems and applications that scale well, and which can successfully meet the demands of changing times and contexts. The topics under each track have been carefully selected to highlight certain qualitative aspects of applications and systems, such as scalability, flexibility, integration, efficiency and context awareness. The first section (Agile Software Development) includes six contributions that address related issues, including risk management, test case prioritization and tools, open source software reliability and predicting the change proneness of software. The second section (Data Management) includes discussions on myriad issues, such as extending database caches using solid-state devices, efficient data transmission, healthcare applications and data security. In turn, the third section (Machine Learning) gathers papers that investigate ML algorithms and present their specific applications such as portfolio optimization, disruption classification and outlier detection. The fourth section (Web Intelligence) covers emerging applications such as metaphor detection, language identification and sentiment analysis, and brings to the fore web security issues such as fraud detection and trust/reputation systems. In closing, the fifth section (Computing in Education) focuses on various aspects of computer-aided pedagogical methods.

Download or read book Advanced Hybrid Information Processing written by Shuai Liu and published by Springer Nature. This book was released on 2022-01-18 with total page 753 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set constitutes the post-conference proceedings of the 5th EAI International Conference on Advanced Hybrid Information Processing, ADHIP 2021, held in October 2021. Due to COVID-19 the conference was held virtually. The 94 papers presented were selected from 254 submissions and focus on theory and application of hybrid information processing technology for smarter and more effective research and application. The theme of ADHIP 2020 was “Social hybrid data processing”. The papers are named in topical sections as follows: Intelligent algorithms in complex environment; AI system research and model design; Method research on Internet of Things technology; Research and analysis with intelligent education.

Download or read book Visual Analysis of Humans written by Thomas B. Moeslund and published by Springer Science & Business Media. This book was released on 2011-10-08 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique text/reference provides a coherent and comprehensive overview of all aspects of video analysis of humans. Broad in coverage and accessible in style, the text presents original perspectives collected from preeminent researchers gathered from across the world. In addition to presenting state-of-the-art research, the book reviews the historical origins of the different existing methods, and predicts future trends and challenges. Features: with a Foreword by Professor Larry Davis; contains contributions from an international selection of leading authorities in the field; includes an extensive glossary; discusses the problems associated with detecting and tracking people through camera networks; examines topics related to determining the time-varying 3D pose of a person from video; investigates the representation and recognition of human and vehicular actions; reviews the most important applications of activity recognition, from biometrics and surveillance, to sports and driver assistance.

Download or read book Computer Vision Metrics written by Scott Krig and published by Apress. This book was released on 2014-06-14 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors actually work, how they are designed, with observations about tuning the methods for achieving robustness and invariance targets for specific applications. The survey is broader than it is deep, with over 540 references provided to dig deeper. The taxonomy includes search methods, spectra components, descriptor representation, shape, distance functions, accuracy, efficiency, robustness and invariance attributes, and more. Rather than providing ‘how-to’ source code examples and shortcuts, this book provides a counterpoint discussion to the many fine opencv community source code resources available for hands-on practitioners.

Download or read book Spatiotemporal Modeling and Analysis in Marine Science written by Junyu He and published by Frontiers Media SA. This book was released on 2023-11-29 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the development of earth observation technologies (such as satellite remote sensing, unmanned aerial vehicle, autonomous underwater vehicle, etc.), an era of big data with important and non-negligible spatial/temporal attributes comes. Novel and rigorous spatiotemporal methodologies and models are needed to process and analyze marine big data. Since many marine environmental processes, such as pollutants diffusion, algae distributions etc., vary or evolve across spatiotemporal domains, detecting the distributions and patterns of marine fauna and, particularly in the coastal regions, will improve our understanding of marine systems and can be beneficial in marine environmental management. The goals of this Research Topic, therefore, are two-fold: (a) to develop methodologies and models in theory and applications, including spatiotemporal geostatistics, geographic information system, deep learning, etc.; (b) to quantitatively gain the knowledge of the marine environment. This Research Topic will provide a platform for researchers to share and exchange their new knowledge gained in a spatiotemporal domain of marine or coastal regions. This Research Topic will cover, but is not limited to, the following areas: • Spatiotemporal variations of physical/chemical/biological indicators (such as chlorophyll, temperature, salinity, colorful dissolved organic matter, suspended solids, nutrients, microplastic, etc.) in marine. • Spatiotemporal variations of potential fishing grounds in marine. • Spatiotemporal variations of the ecosystems in coastal regions, such as salt marshes, mangroves, seagrass, macroalgae, etc. • Spatiotemporal distributions of the pollutants (such as heavy metals, polycyclic aromatic hydrocarbon, etc.) in marine and sediments. • Spatiotemporal evolution pattern modeling and prediction of the marine disasters and abnormal phenomena (such as algal bloom, typhoons, SST anomalies, etc).

Download or read book Remote Sensing Imagery written by Florence Tupin and published by John Wiley & Sons. This book was released on 2014-02-19 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dedicated to remote sensing images, from their acquisition to their use in various applications, this book covers the global lifecycle of images, including sensors and acquisition systems, applications such as movement monitoring or data assimilation, and image and data processing. It is organized in three main parts. The first part presents technological information about remote sensing (choice of satellite orbit and sensors) and elements of physics related to sensing (optics and microwave propagation). The second part presents image processing algorithms and their specificities for radar or optical, multi and hyper-spectral images. The final part is devoted to applications: change detection and analysis of time series, elevation measurement, displacement measurement and data assimilation. Offering a comprehensive survey of the domain of remote sensing imagery with a multi-disciplinary approach, this book is suitable for graduate students and engineers, with backgrounds either in computer science and applied math (signal and image processing) or geo-physics. About the Authors Florence Tupin is Professor at Telecom ParisTech, France. Her research interests include remote sensing imagery, image analysis and interpretation, three-dimensional reconstruction, and synthetic aperture radar, especially for urban remote sensing applications. Jordi Inglada works at the Centre National d’Études Spatiales (French Space Agency), Toulouse, France, in the field of remote sensing image processing at the CESBIO laboratory. He is in charge of the development of image processing algorithms for the operational exploitation of Earth observation images, mainly in the field of multi-temporal image analysis for land use and cover change. Jean-Marie Nicolas is Professor at Telecom ParisTech in the Signal and Imaging department. His research interests include the modeling and processing of synthetic aperture radar images.