Knowledge Based Interpretation Of Outdoor Natural Color Scenes

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

The three volume set LNCS 5994, LNCS 5995, and LNCS 5996 constitutes the thoroughly refereed post-conference proceedings of the 9th Asian Conference on Computer Vision, ACCV 2009, held in Xi'an, China, in September 2009. The 35 revised full papers and 130 revised poster papers of the three volumes were carefully reviewed and seleceted from 670 submissions. The papers are organized in topical sections on multiple view and stereo, face and pose analysis, motion analysis and tracking, segmentation, feature extraction and object detection, image enhancement and visual attention, machine learning algorithms for vision, object categorization and face recognition, biometrics and surveillance, stereo, motion analysis, and tracking, segmentation, detection, color and texture, as well as machine learning, recognition, biometrics and surveillance.

By Raymond J. Mooney.

IbPRIA 2005 (Iberian Conference on Pattern Recognition and Image Analysis) was the second of a series of conferences jointly organized every two years by the Portuguese and Spanish Associations for Pattern Recognition (APRP, AERFAI), with the support of the International Association for Pattern Recognition (IAPR). This year, IbPRIA was hosted by the Institute for Systems and Robotics and the Geo-systems Center of the Instituto Superior Tecn ́ ico and it was held in Estoril, Por- gal. It provided the opportunity to bring together researchers from all over the world to discuss some of the most recent advances in pattern recognition and all areas of video, image and signal processing. There was a very positive response to the Call for Papers for IbPRIA 2005. We - ceived 292 full papers from 38 countries and 170 were accepted for presentation at the conference. The high quality of the scienti?c program of IbPRIA 2005 was due ?rst to the authors who submitted excellent contributions and second to the dedicated colla- ration of the international Program Committee and the other researchers who reviewed the papers. Each paper was reviewed by two reviewers, in a blind process. We would like to thank all the authors for submitting their contributions and for sharing their - search activities. We are particularly indebted to the Program Committee members and to all the reviewers for their precious evaluations, which permitted us to set up this publication.

This book contains papers presented at the NATO Advanced Research Workshop on "Real-time Object and Environment Measurement and Classification" held in Hotel Villa del Mare, Maratea, Italy, August 31 - September 3, 1987. This workshop was organized under the NATO Special Programme on Sensory Systems for Robotic Control. Professor Eric Backer, Delft University of Technology, The Netherlands and Professor Erdal Panayirci, Technical University of Istanbul, Turkey were the members of the organizing committee for this workshop. There were four major themes of this workshop: Real-time Requirements, Feature Measurement, Object Representation and Recognition, and Architecture for Measurement and Classification. A total of twenty-five technical presentations were made. These talks covered a wide spectrum of topics including hardware implementation of specific vision algorithms, a complete vision system for object tracking and inspection, using three cameras (trinocular stereo) for feature measurement, neural network for object recognition, integration of CAD (Computer-Aided Design) and vision systems, and the use of pyramid architectures for solving varioos computer vision problems.