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Boosting For Generic 2d 3d Object Recognition
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Book Synopsis Boosting for Generic 2D/3D Object Recognition by : Doaa Abd al-Kareem Mohammed Hegazy
Download or read book Boosting for Generic 2D/3D Object Recognition written by Doaa Abd al-Kareem Mohammed Hegazy and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generic object recognition is an important function of the human visual system. For an artificial vision system to be able to emulate the human perception abilities, it should also be able to perform generic object recognition. In this thesis, we address the generic object recognition problem and present different approaches and models which tackle different aspects of this difficult problem. First, we present a model for generic 2D object recognition from complex 2D images. The model exploits only appearance-based information, in the form of a combination of texture and color cues, for binary classification of 2D object classes. Learning is accomplished in a weakly supervised manner using Boosting. However, we live in a 3D world and the ability to recognize 3D objects is very important for any vision system. Therefore, we present a model for generic recognition of 3D objects from range images. Our model makes use of a combination of simple local shape descriptors extracted from range images for recognizing 3D object categories, as shape is an important information provided by range images. Moreover, we present a novel dataset for generic object recognition that provides 2D and range images about different object classes using a Time-of-Flight (ToF) camera.
Book Synopsis Boosting Unsupervised Domain Adaptation for 3D Object Detection in Point Clouds Via 2D Image Semantic Information by : 谷俊杰
Download or read book Boosting Unsupervised Domain Adaptation for 3D Object Detection in Point Clouds Via 2D Image Semantic Information written by 谷俊杰 and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Generic Object Recognition Using Form & Function by : Louise Stark
Download or read book Generic Object Recognition Using Form & Function written by Louise Stark and published by World Scientific. This book was released on 1996 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph provides a detailed record of the ?GRUFF? research project. The goal of the GRUFF project is to develop techniques for robotic vision systems to recognize objects by reasoning about their intended function rather than matching to a pre-defined database of 2-D object appearances or 3-D object shapes. The contributions of this work are: a demonstration of the feasibility of the ?form and function? approach to reasoning about 3-D shapes; a demonstration of the concept of using a small number of knowledge primitives as component building blocks in creating a function-based definition of an object category; and an indexing mechanism to make processing for recognition more efficient without any substantial decrease in correctness of classification. Results are given for the analysis of over 500 3-D shape descriptions created with a solid modeling tool and over 200 shape descriptions extracted from real laser range finder images.
Author :Eduardo Bayro Corrochano Publisher :Springer Science & Business Media ISBN 13 :3642102670 Total Pages :1082 pages Book Rating :4.6/5 (421 download)
Book Synopsis Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications by : Eduardo Bayro Corrochano
Download or read book Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications written by Eduardo Bayro Corrochano and published by Springer Science & Business Media. This book was released on 2009-10-26 with total page 1082 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th Iberoamerican Congress on Pattern Recognition, CIARP 2009, held in Guadalajara, Mexico, in November 2009. The 64 revised full papers presented together with 44 posters were carefully reviewed and selected from 187 submissions. The papers are organized in topical sections on image coding, processing and analysis; segmentation, analysis of shape and texture; geometric image processing and analysis; analysis of signal, speech and language; document processing and recognition; feature extraction, clustering and classification; statistical pattern recognition; neural networks for pattern recognition; computer vision; video segmentation and tracking; robot vision; intelligent remote sensing, imagery research and discovery techniques; intelligent computing for remote sensing imagery; as well as intelligent fusion and classification techniques.
Book Synopsis Feature Extraction and 2D/3D Object Recognition Using Geometric Invariants by : Yonggen Zhu
Download or read book Feature Extraction and 2D/3D Object Recognition Using Geometric Invariants written by Yonggen Zhu and published by . This book was released on 1996 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Representations and Techniques for 3D Object Recognition and Scene Interpretation by : Derek Hoiem
Download or read book Representations and Techniques for 3D Object Recognition and Scene Interpretation written by Derek Hoiem and published by Morgan & Claypool Publishers. This book was released on 2011 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physical scenes from images. The second section introduces representations for 3D object categories that account for the intrinsically 3D nature of objects and provide robustness to change in viewpoints. The third section discusses strategies to unite inference of scene geometry and object pose and identity into a coherent scene interpretation. Each section broadly surveys important ideas from cognitive science and artificial intelligence research, organizes and discusses key concepts and techniques from recent work in computer vision, and describes a few sample approaches in detail. Newcomers to computer vision will benefit from introductions to basic concepts, such as single-view geometry and image classification, while experts and novices alike may find inspiration from the book's organization and discussion of the most recent ideas in 3D scene understanding and 3D object recognition. Specific topics include: mathematics of perspective geometry; visual elements of the physical scene, structural 3D scene representations; techniques and features for image and region categorization; historical perspective, computational models, and datasets and machine learning techniques for 3D object recognition; inferences of geometrical attributes of objects, such as size and pose; and probabilistic and feature-passing approaches for contextual reasoning about 3D objects and scenes. Table of Contents: Background on 3D Scene Models / Single-view Geometry / Modeling the Physical Scene / Categorizing Images and Regions / Examples of 3D Scene Interpretation / Background on 3D Recognition / Modeling 3D Objects / Recognizing and Understanding 3D Objects / Examples of 2D 1/2 Layout Models / Reasoning about Objects and Scenes / Cascades of Classifiers / Conclusion and Future Directions
Book Synopsis Handbook of Face Recognition by : Stan Z. Li
Download or read book Handbook of Face Recognition written by Stan Z. Li and published by Springer Science & Business Media. This book was released on 2011-08-22 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: This highly anticipated new edition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational face recognition systems. After a thorough introductory chapter, each of the following chapters focus on a specific topic, reviewing background information, up-to-date techniques, and recent results, as well as offering challenges and future directions. Features: fully updated, revised and expanded, covering the entire spectrum of concepts, methods, and algorithms for automated face detection and recognition systems; provides comprehensive coverage of face detection, tracking, alignment, feature extraction, and recognition technologies, and issues in evaluation, systems, security, and applications; contains numerous step-by-step algorithms; describes a broad range of applications; presents contributions from an international selection of experts; integrates numerous supporting graphs, tables, charts, and performance data.
Book Synopsis 3D Object Recognition Based on Constrained 2D Views by : Levente Toth
Download or read book 3D Object Recognition Based on Constrained 2D Views written by Levente Toth and published by . This book was released on 1998 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Real Time Object Recognition and Tracking Using 2D/3D Images by : Seyed Eghbal Ghobadi
Download or read book Real Time Object Recognition and Tracking Using 2D/3D Images written by Seyed Eghbal Ghobadi and published by . This book was released on 2010 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Learning in Medical Imaging by : Guorong Wu
Download or read book Machine Learning in Medical Imaging written by Guorong Wu and published by Springer. This book was released on 2013-09-18 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Medical Imaging, MLMI 2013, held in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, in Nagoya, Japan, in September 2013. The 32 contributions included in this volume were carefully reviewed and selected from 57 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.
Book Synopsis Three-Dimensional Object Recognition Systems by : Anil K Jain
Download or read book Three-Dimensional Object Recognition Systems written by Anil K Jain and published by . This book was released on 1993-05-05 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: The design and construction of three-dimensional [3-D] object recognition systems has long occupied the attention of many computer vision researchers. The variety of systems that have been developed for this task is evidence both of its strong appeal to researchers and its applicability to modern manufacturing, industrial, military, and consumer environments. 3-D object recognition is of interest to scientists and engineers in several different disciplines due to both a desire to endow computers with robust visual capabilities, and the wide applications which would benefit from mature and robust vision systems. However, 3-D object recognition is a very complex problem, and few systems have been developed for actual production use; most existing systems have been developed for experimental use by researchers only. This edited collection of papers summarizes the state of the art in 3-D object recognition using examples of existing 3-D systems developed by leading researchers in the field. While most chapters describe a complete object recognition system, chapters on biological vision, sensing, and early processing are also included. The volume will serve as a valuable reference source for readers who are involved in implementing model-based object recognition systems, stimulating the cross-fertilisation of ideas in the various domains. The variety of topics on Image Communication is so broad that no one can be a specialist in all the topics, and the whole area is beyond the scope of a single volume, while the requirement of up to date information is ever increasing. This new closed-end book series is intended both as a comprehensive reference for those already active in the area of Image Communication, as well as providing newcomers with a foothold for commencing research. Each volume will comprise a state of the art work on the editor's/author's area of expertise, containing information until now scattered in many journals and proceedings.
Book Synopsis Learning Grouping Strategies for 2D and 3D Object Recognition by :
Download or read book Learning Grouping Strategies for 2D and 3D Object Recognition written by and published by . This book was released on 1996 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Schema Learning System (SLS) automatically assembles task specific object recognition programs from existing IU algorithms. SLS brings together two emerging technologies; image understanding and machine learning, to automatically build customized procedures for recognizing and extracting specific object classes in constrained contexts. This paper describes the representations and algorithms underlying SLS, and presents an example of SLS learning to recognize rooftops in aerial images of Ft. Hood. This task is the first of several tasks from the ARPA/ORD sponsored RADIUS project that SLS is intended to learn without human interaction. In later experiments, SLS will be tasked to automatically construct 3D models of buildings and other objects of interest from overlapping aerial images.
Download or read book Biometric Recognition written by Jie Zhou and published by Springer. This book was released on 2017-10-17 with total page 764 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recognition, CCBR 2017, held in Shenzhen, China, in October 2017. The 15 full papers and 65 poster papers presented in this book were carefully reviewed and selected from 138 submissions. The papers are organized in topical sections on face; fingerprint, palm-print and vascular biometrics; iris; gesture and gait; emerging biometrics; voice and speech; video surveillance; feature extraction and classification theory; behavioral biometrics.
Book Synopsis Image Analysis and Processing - ICIAP 2017 by : Sebastiano Battiato
Download or read book Image Analysis and Processing - ICIAP 2017 written by Sebastiano Battiato and published by Springer. This book was released on 2017-10-11 with total page 788 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNCS 10484 and 10485 constitutes the refereed proceedings of the 19th International Conference on Image Analysis and Processing, ICIAP 2017, held in Catania, Italy, in September 2017. The 138 papers presented were carefully reviewed and selected from 229 submissions. The papers cover both classic and the most recent trends in image processing, computer vision, and pattern recognition, addressing both theoretical and applicative aspects. They are organized in the following topical sections: video analysis and understanding; pattern recognition and machine learning; multiview geometry and 3D computer vision; image analysis, detection and recognition; multimedia; biomedical and assistive technology; information forensics and security; imaging for cultural heritage and archaeology; and imaging solutions for improving the quality of life.
Book Synopsis Medical Image Recognition, Segmentation and Parsing by : S. Kevin Zhou
Download or read book Medical Image Recognition, Segmentation and Parsing written by S. Kevin Zhou and published by Academic Press. This book was released on 2015-12-11 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of- the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image. Written by top experts in Medical Imaging, this book is ideal for university researchers and industry practitioners in medical imaging who want a complete reference on key methods, algorithms and applications in medical image recognition, segmentation and parsing of multiple objects. Learn: Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects Methods and theories for medical image recognition, segmentation and parsing of multiple objects Efficient and effective machine learning solutions based on big datasets Selected applications of medical image parsing using proven algorithms Provides a comprehensive overview of state-of-the-art research on medical image recognition, segmentation, and parsing of multiple objects Presents efficient and effective approaches based on machine learning paradigms to leverage the anatomical context in the medical images, best exemplified by large datasets Includes algorithms for recognizing and parsing of known anatomies for practical applications
Book Synopsis Computer Vision for Driver Assistance by : Mahdi Rezaei
Download or read book Computer Vision for Driver Assistance written by Mahdi Rezaei and published by Springer. This book was released on 2017-02-06 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Visual Object Recognition by : Kristen Grauman
Download or read book Visual Object Recognition written by Kristen Grauman and published by Morgan & Claypool Publishers. This book was released on 2011 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: The visual recognition problem is central to computer vision research. From robotics to information retrieval, many desired applications demand the ability to identify and localize categories, places, and objects. This tutorial overviews computer vision algorithms for visual object recognition and image classification. We introduce primary representations and learning approaches, with an emphasis on recent advances in the field. The target audience consists of researchers or students working in AI, robotics, or vision who would like to understand what methods and representations are available for these problems. This lecture summarizes what is and isn't possible to do reliably today, and overviews key concepts that could be employed in systems requiring visual categorization. Table of Contents: Introduction / Overview: Recognition of Specific Objects / Local Features: Detection and Description / Matching Local Features / Geometric Verification of Matched Features / Example Systems: Specific-Object Recognition / Overview: Recognition of Generic Object Categories / Representations for Object Categories / Generic Object Detection: Finding and Scoring Candidates / Learning Generic Object Category Models / Example Systems: Generic Object Recognition / Other Considerations and Current Challenges / Conclusions
