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This book provides a deep analysis and wide coverage of the very strong trend in computer vision and visual indexing and retrieval, covering such topics as incorporation of models of Human Visual attention into analysis and retrieval tasks. It makes the bridge between psycho-visual modelling of Human Visual System and the classical and most recent models in visual content indexing and retrieval. The large spectrum of visual tasks, such as recognition of textures in static images, of actions in video content, image retrieval, different methods of visualization of images and multimedia content based on visual saliency are presented by the authors. Furthermore, the interest in visual content is modelled with the means of the latest classification models such as Deep Neural Networks is also covered in this book. This book is an exceptional resource as a secondary text for researchers and advanced level students, who are involved in the very wide research in computer vision, visual information indexing and retrieval. Professionals working in this field will also be interested in this book as a reference.
The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic. The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 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.
Recent years have witnessed important advancements in our understanding of the psychological underpinnings of subjective properties of visual information, such as aesthetics, memorability, or induced emotions. Concurrently, computational models of objective visual properties such as semantic labelling and geometric relationships have made significant breakthroughs using the latest achievements in machine learning and large-scale data collection. There has also been limited but important work exploiting these breakthroughs to improve computational modelling of subjective visual properties. The time is ripe to explore how advances in both of these fields of study can be mutually enriching and lead to further progress. This book combines perspectives from psychology and machine learning to showcase a new, unified understanding of how images and videos influence high-level visual perception - particularly interestingness, affective values and emotions, aesthetic values, memorability, novelty, complexity, visual composition and stylistic attributes, and creativity. These human-based metrics are interesting for a very broad range of current applications, ranging from content retrieval and search, storytelling, to targeted advertising, education and learning, and content filtering. Work already exists in the literature that studies the psychological aspects of these notions or investigates potential correlations between two or more of these human concepts. Attempts at building computational models capable of predicting such notions can also be found, using state-of-the-art machine learning techniques. Nevertheless their performance proves that there is still room for improvement, as the tasks are by nature highly challenging and multifaceted, requiring thought on both the psychological implications of the human concepts, as well as their translation to machines.
This book provides the reader with the fundamental knowledge in the area of deep learning with application to visual content mining. The authors give a fresh view on Deep learning approaches both from the point of view of image understanding and supervised machine learning. It contains chapters which introduce theoretical and mathematical foundations of neural networks and related optimization methods. Then it discusses some particular very popular architectures used in the domain: convolutional neural networks and recurrent neural networks. Deep Learning is currently at the heart of most cutting edge technologies. It is in the core of the recent advances in Artificial Intelligence. Visual information in Digital form is constantly growing in volume. In such active domains as Computer Vision and Robotics visual information understanding is based on the use of deep learning. Other chapters present applications of deep learning for visual content mining. These include attention mechanisms in deep neural networks and application to digital cultural content mining. An additional application field is also discussed, and illustrates how deep learning can be of very high interest to computer-aided diagnostics of Alzheimer’s disease on multimodal imaging. This book targets advanced-level students studying computer science including computer vision, data analytics and multimedia. Researchers and professionals working in computer science, signal and image processing may also be interested in this book.
This book constitutes the refereed proceedings of the 8th International Workshop on Visual Content Processing and Representation, VLBV 2003, held in Madrid, Spain in September 2003. The 38 revised full papers presented together with 4 panel summaries were carefully reviewed and selected from 89 submissions. The papers address all current issues in video and image analysis, representation and coding, communications and delivery, consumption, synthesis, protection, adaptation, classification, and personalization.
This book constitutes the thoroughly refereed post-proceedings of the 9th International Conference on Visual Information Systems, VISUAL 2007, held in Shanghai, China, in June 2007. The papers are organized in topical section on image and video retrieval, visual biometrics, intelligent visual information processing, visual data mining, ubiquitous and mobile visual information systems, semantics, 2D/3D graphical visual data retrieval, and applications of visual information systems.
July 19-21, 2018 Rome, Italy Key Topics : Imaging and Image Processing, Multimedia Cloud and Big Data, Multimedia IoT, Multimedia Systems & Services, Computer Games Design & Development, Multimedia Applications, Computer Graphics & Animation, Compter Vision and Pattern Recognition, Virtual Reality & Augmented Reality, Artificial Intelligence & Machine Learning, Natural language processing & Tensorflow, Artificial Intelligence for Bussines, Neural Networks, Human Computer Interaction and Visualization, Artificial Intelligence & Multimedia Technologies in Healthcare,
Comprises 25 revised full papers presented at the 8th International Conference on Visual Information Systems, VISUAL 2005, held in Amsterdam, The Netherlands in July 2005. These represent the current state of the art of visual information processing, feature extraction and aggregation at semantic level and content-based retrieval, as well as the study of user intention in query processing, and issues of delivery and consumption of multimedia content.
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.
Theseproceedingscontaintherefereedfulltechnicalpaperspresentedatthe26th Annual European Conference on Information Retrieval (ECIR 2004). ECIR is theannualconferenceoftheBritishComputerSociety’sspecialistgroupinInf- mation Retrieval. This year the conference was held at the School of Computing and Technology at the University of Sunderland. ECIR began life as the - nual Colloquium on Information Retrieval Research. The colloquium was held in the UK each year until 1998 when the event was held in Grenoble, France. Since then the conference venue has alternated between the United Kingdom and Continental Europe, and the event was renamed the European Conference on Information Retrieval. In recent years, ECIR has continued to grow and has become the major European forum for the discussion of research in the ?eld of Information Retrieval. To mark this metamorphosis from a small informal c- loquium to a major event in the IR research calendar, the BCS-IRSG decided to rename the event to the European Conference on Information Retrieval. ECIR2004received88fullpapersubmissions,fromacrossEuropeandfurther a?eldincludingNorthAmerica,ChinaandAustralia,atestamenttothegrowing popularity and reputation of the conference. Out of the 88 submitted papers, 28 were accepted for presentation. All papers were reviewed by at least three reviewers. Among the accepted papers 11 have a student as the primary author, illustrating that the traditional student focus of the original colloquium is alive today.