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Here are the refereed proceedings of the 5th International Conference on Image and Video Retrieval, CIVR 2006, held in Singapore in July 2006. Presents 18 revised full papers and 30 poster papers, together with extended abstracts of 5 papers of 1 special session and those of 10 demonstration papers. These cover interactive image and video retrieval, semantic image retrieval, visual feature analysis, learning and classification, image and video retrieval metrics, and machine tagging.
This 8-volumes set constitutes the refereed of the 25th International Conference on Pattern Recognition Workshops, ICPR 2020, held virtually in Milan, Italy and rescheduled to January 10 - 11, 2021 due to Covid-19 pandemic. The 416 full papers presented in these 8 volumes were carefully reviewed and selected from about 700 submissions. The 46 workshops cover a wide range of areas including machine learning, pattern analysis, healthcare, human behavior, environment, surveillance, forensics and biometrics, robotics and egovision, cultural heritage and document analysis, retrieval, and women at ICPR2020.
Images and video play a crucial role in visual information systems and multimedia. There is an extraordinary number of applications of such systems in entertainment, business, art, engineering, and science. Such applications often involved large image and video collections, and therefore, searching for images and video in large collections is becoming an important operation. Because of the size of such databases, efficiency is crucial. We strongly believe that image and video retrieval need an integrated approach from fields such as image processing, shape processing, perception, database indexing, visualization, and querying, etc. This book contains a selection of results that was presented at the Dagstuhl Seminar on Content-Based Image and Video Retrieval, in December 1999. The purpose of this seminar was to bring together people from the various fields, in order to promote information exchange and interaction among researchers who are interested in various aspects of accessing the content of image and video data. The book provides an overview of the state of the art in content-based image and video retrieval. The topics covered by the chapters are integrated system aspects, as well as techniques from image processing, computer vision, multimedia, databases, graphics, signal processing, and information theory. The book will be of interest to researchers and professionals in the fields of multimedia, visual information (database) systems, computer vision, and information retrieval.
First of all, we want to congratulate two new research communities from M- ico and Brazil that have recently joined the Iberoamerican community and the International Association for Pattern Recognition. We believe that the series of congresses that started as the “Taller Iberoamericano de Reconocimiento de Patrones (TIARP)”, and later became the “Iberoamerican Congress on Pattern Recognition (CIARP)”, has contributed to these groupconsolidatione?orts. We hope that in the near future all the Iberoamerican countries will have their own groups and associations to promote our areas of interest; and that these congresses will serve as the forum for scienti?c research exchange, sharing of - pertise and new knowledge, and establishing contacts that improve cooperation between research groups in pattern recognition and related areas. CIARP 2004 (9th Iberoamerican Congress on Pattern Recognition) was the ninthinaseriesofpioneeringcongressesonpatternrecognitionintheIberoam- ican community. As in the previous year, CIARP 2004 also included worldwide participation. It took place in Puebla, Mexico. The aim of the congress was to promote and disseminate ongoing research and mathematical methods for pattern recognition, image analysis, and applications in such diverse areas as computer vision, robotics, industry, health, entertainment, space exploration, telecommunications, data mining, document analysis,and natural languagep- cessing and recognition, to name a few.
This book offers a comprehensive introduction to advanced methods for image and video analysis and processing. It covers deraining, dehazing, inpainting, fusion, watermarking and stitching. It describes techniques for face and lip recognition, facial expression recognition, lip reading in videos, moving object tracking, dynamic scene classification, among others. The book combines the latest machine learning methods with computer vision applications, covering topics such as event recognition based on deep learning,dynamic scene classification based on topic model, person re-identification based on metric learning and behavior analysis. It also offers a systematic introduction to image evaluation criteria showing how to use them in different experimental contexts. The book offers an example-based practical guide to researchers, professionals and graduate students dealing with advanced problems in image analysis and computer vision.
This volume is a post-event proceedings volume and contains selected papers based on presentations given, and vivid discussions held, during two workshops held in Taormina in 2003 and 2004. The 30 thoroughly revised papers presented are organized in the following topical sections: recognition of specific objects, recognition of object categories, recognition of object categories with geometric relations, and joint recognition and segmentation.
This book constitutes the refereed proceedings of the 4th International Conference on Image Analysis and Recognition, ICIAR 2007, held in Montreal, Canada, in August 2007. The 71 revised full papers and 44 revised poster papers presented were carefully reviewed and selected from 261 submissions. The papers are organized in topical sections on image restoration and enhancement, image and video processing and analysis, image segmentation, computer vision, pattern recognition for image analysis, shape and matching, motion analysis, tracking, image retrieval and indexing, image and video coding and encryption, biometrics, biomedical image analysis, and applications.
This book presents cutting-edge research on various ways to bridge the semantic gap in image and video analysis. The respective chapters address different stages of image processing, revealing that the first step is a future extraction, the second is a segmentation process, the third is object recognition, and the fourth and last involve the semantic interpretation of the image. The semantic gap is a challenging area of research, and describes the difference between low-level features extracted from the image and the high-level semantic meanings that people can derive from the image. The result greatly depends on lower level vision techniques, such as feature selection, segmentation, object recognition, and so on. The use of deep models has freed humans from manually selecting and extracting the set of features. Deep learning does this automatically, developing more abstract features at the successive levels. The book offers a valuable resource for researchers, practitioners, students and professors in Computer Engineering, Computer Science and related fields whose work involves images, video analysis, image interpretation and so on.
This book constitutes the refereed proceedings of the Third Pacific Rim Symposium on Image and Video Technology, PSIVT 2008, held in Tokyo, Japan, in January 2009. The 39 revised full papers and 57 posters were carefully reviewed and selected from 247 submissions. The symposium features 8 major themes including all aspects of image and video technology: image sensors and multimedia hardware; graphics and visualization; image and video analysis; recognition and retrieval; multi-view imaging and processing; computer vision applications; video communications and networking; and multimedia processing. The papers are organized in topical sections on faces and pedestrians; panoramic images; local image analysis; organization and grouping; multiview geometry; detection and tracking; computational photography and forgeries; coding and steganography; recognition and search; and reconstruction and visualization.
Written by leading researchers, the 2nd Edition of the Dictionary of Computer Vision & Image Processing is a comprehensive and reliable resource which now provides explanations of over 3500 of the most commonly used terms across image processing, computer vision and related fields including machine vision. It offers clear and concise definitions with short examples or mathematical precision where necessary for clarity that ultimately makes it a very usable reference for new entrants to these fields at senior undergraduate and graduate level, through to early career researchers to help build up knowledge of key concepts. As the book is a useful source for recent terminology and concepts, experienced professionals will also find it a valuable resource for keeping up to date with the latest advances. New features of the 2nd Edition: Contains more than 1000 new terms, notably an increased focus on image processing and machine vision terms; Includes the addition of reference links across the majority of terms pointing readers to further information about the concept under discussion so that they can continue to expand their understanding; Now available as an eBook with enhanced content: approximately 50 videos to further illustrate specific terms; active cross-linking between terms so that readers can easily navigate from one related term to another and build up a full picture of the topic in question; and hyperlinked references to fully embed the text in the current literature.