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.

In the last few years we have observed an explosive growth of multimedia computing, communication and applications. This revolution is transforming the way people live, work, and interact with each other, and is impacting the way business, government services, education, entertainment and healthcare are operating. Yet, several issues related to modeling, specification, analysis and design of distributed multimedia database systems and multimedia information retrieval are still challenging to both researchers and praclitioners. Distributed Multimedia Databases: Techniques and Applications points out these challenges and provides valuable suggestions toward the necessary solutions, by focusing on multimedia database techniques.

KI 2008 was the 31st Annual German Conference on Arti?cial Intelligence held September 23–26 at the University of Kaiserslautern and the German Research Center for Arti?cial Intelligence DFKI GmbH in Kaiserslautern, Germany. The conference series started in 1975 with the German Workshop on AI (GWAI), which took place in Bonn, and represents the ?rst forum of its type for the German AI Community. Over the years AI has become a major ?eld in c- puter scienceinGermanyinvolvinga numberof successfulprojects thatreceived much international attention. Today KI conferences are international forums where participants from academia and industry from all over the world meet to exchange their recent research results and to discuss trends in the ?eld. Since 1993 the meeting has been called the “Annual German Conference on Arti?cial Intelligence,” designated by the German acronym KI. This volume contains the papers selected out of 77 submissions, including a number of submissions from outside German-speaking countries. In total, 15 submissions (19%) were accepted for oral and 30 (39%) for poster presentation. Oralpresentationsattheconferenceweresingletrack. Becauseofthis,thechoice of presentation form (oral, poster) was based on how well reviews indicated that the paper would ?t into one or the other format. The proceedings allocate the same space to both types of papers. In addition, we selected six papers that show high application potential - scribing systems or prototypical implementations of innovative AI technologies. They are also included in this volume as two-page extended abstracts.

This volume provides a collection of sixteen articles containing review and new material. In a unified way, they describe the recent development of theories and methodologies in pattern recognition, image processing and vision using fuzzy logic, artificial neural networks, genetic algorithms, rough sets and wavelets with significant real life applications. The book details the theory of granular computing and the role of a rough-neuro approach as a way of computing with words and designing intelligent recognition systems. It also demonstrates applications of the soft computing paradigm to case based reasoning, data mining and bio-informatics with a scope for future research. The contributors from around the world present a balanced mixture of current theory, algorithms and applications, making the book an extremely useful resource for students and researchers alike. Contents: Pattern Recognition: Multiple Classifier Systems; Building Decision Trees from the Fourier Spectrum of a Tree Ensemble; Clustering Large Data Sets; Multi-objective Variable String Genetic Classifier: Application to Remote Sensing Imagery; Image Processing and Vision: Dissimilarity Measures Between Fuzzy Sets or Fuzzy Structures; Early Vision: Concepts and Algorithms; Self-organizing Neural Network for Multi-level Image Segmentation; Geometric Transformation by Moment Method with Wavelet Matrix; New Computationally Efficient Algorithms for Video Coding; Soft Computing for Computational Media Aesthetics: Analyzing Video Content for Meaning; Granular Computing and Case Based Reasoning: Towards Granular Multi-agent Systems; Granular Computing and Pattern Recognition; Case Base Maintenance: A Soft Computing Perspective; Real Life Applications: Autoassociative Neural Network Models for Pattern Recognition Tasks in Speech and Image; Protein Structure Prediction Using Soft Computing; Pattern Classification for Biological Data Mining. Readership: Upper level undergraduates, graduates, researchers, academics and industrialists.

This book constitutes the refereed proceedings of the Second International Conference on Semantics and Digital Media Technologies, SAMT 2007, held in Genoa, Italy, in December 2007. The conference brings together forums, projects, institutions and individuals investigating the integration of knowledge, semantics and low-level multimedia processing, including new emerging media and application areas. The papers are organized in topical sections.

Novel processing and searching tools for the management of new multimedia documents have developed. Multimedia Information Retrieval (MIR) is an organic system made up of Text Retrieval (TR); Visual Retrieval (VR); Video Retrieval (VDR); and Audio Retrieval (AR) systems. So that each type of digital document may be analysed and searched by the elements of language appropriate to its nature, search criteria must be extended. Such an approach is known as the Content Based Information Retrieval (CBIR), and is the core of MIR. This novel content-based concept of information handling needs to be integrated with more traditional semantics. Multimedia Information Retrieval focuses on the tools of processing and searching applicable to the content-based management of new multimedia documents. Translated from Italian by Giles Smith, the book is divided into two parts. Part one discusses MIR and related theories, and puts forward new methodologies; part two reviews various experimental and operating MIR systems, and presents technical and practical conclusions. - Gives a complete, organic picture of MIR and CBIR - Proposes a novel conceptualisation around the ideas of Information Retrieval (IR) and digital document management in the context of Library and Information Science (LIS) - Relevant for both library and information science and information technology specialists