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As our heritage deteriorates through erosion, human error or natural disasters, it has become more important than ever to preserve our past – even if it is in digital form only. This highly relevant work describes thorough research and methods for preserving cultural heritage objects through the use of 3D digital data. These methods were developed via computer vision and computer graphics technologies. They offer a way of passing our heritage down to future generations.
Visual pattern analysis is a fundamental tool in mining data for knowledge. Computational representations for patterns and texture allow us to summarize, store, compare, and label in order to learn about the physical world. Our ability to capture visual imagery with cameras and sensors has resulted in vast amounts of raw data, but using this information effectively in a task-specific manner requires sophisticated computational representations. We enumerate specific desirable traits for these representations: (1) intraclass invariance—to support recognition; (2) illumination and geometric invariance for robustness to imaging conditions; (3) support for prediction and synthesis to use the mo...
This book provides a comprehensive overview of the research on anomaly detection with respect to context and situational awareness that aim to get a better understanding of how context information influences anomaly detection. In each chapter, it identifies advanced anomaly detection and key assumptions, which are used by the model to differentiate between normal and anomalous behavior. When applying a given model to a particular application, the assumptions can be used as guidelines to assess the effectiveness of the model in that domain. Each chapter provides an advanced deep content understanding and anomaly detection algorithm, and then shows how the proposed approach is deviating of the...
Selected, peer reviewed papers from the 2011 International Conference on Advanced Materials and Information Technology Processing (AMITP 2011)