Vorlesung Computer Vision

For the majority of living beeings vision is the most important perception mechanism for orienting themselves in the environment. Therefore, there exists a multitude of attempts to recreate this capability in artificial systems. In contrast to image processing techniques found in industrial applications the aim of such advanced systems for machine vision is to obtain a task-oriented interpretation of a complex scene with as few restrictions as possible concerning the context and the recording conditions. In this lecture advanced techniques of machine vision are covered which to some extent are inspired by cognitive processes known from human visual perception. First, important aspects of imaging processes are introduced with an emphasis on the perception of colors. Afterwards, methods for the extraction of image primitives (e.g. regions and edges) and for the calculation of feature representations (e.g. texture, depth, or motion) are presented. Finally, the lecture focuses on visual perception processes at the boundary between image processing and scene interpretation. Especially, appearance based object recognition techniques and methods for tracking objects in image sequences will be covered. The accompanying tutorials will give students the opportunity to deepen their knowledge of the theoretical concepts presented in the lecture by working on relevant practical problems. LiteraturGonzalez, Rafael C.; Woods, Richard E.: Digital Image Processing, Prentice Hall, 2nd Ed., 2002. Forsyth, David A.; Ponce, Jean: Computer Vision - A Modern Approach, Prentice Hall, 2003. Bemerkung Topical focus areas (Schwerpunktgebiete): 2 (..., Embedded Systems, ...), 7 (Intelligent Systems) Specialization Module (Vertiefungsmodul INF-MA-502) for Master (Applied) Computer Science For up-to-date information on the lecture please refer to the accompanying web page. Gonzalez, Rafael C.; Woods, Richard E.: Digital Image Processing, Prentice Hall, 2nd Ed., 2002. Forsyth, David A.; Ponce, Jean: Computer Vision - A Modern Approach, Prentice Hall, 2003. Bemerkung Topical focus areas (Schwerpunktgebiete): 2 (..., Embedded Systems, ...), 7 (Intelligent Systems) Specialization Module (Vertiefungsmodul INF-MA-502) for Master (Applied) Computer Science For up-to-date information on the lecture please refer to the accompanying web page. Informatik Technische Universität Dortmund SoSe 2012 Lehrstuhl Informatik XII Univ.-Prof. Dr. Fink Gernot