Visual Object Recognition Grauman Kristen Lorraine 1979 Leibe by Grauman, Kristen Lorraine, 1979-, Leibe, Bastian instant download after payment.

The visual recognition problem is central to computer vision research. From robotics to information retrieval, many desired applications demand the ability to identify and localize categories, places, and objects. This tutorial overviews computer vision algorithms for visual object recognition and image classification. We introduce primary representations and learning approaches, with an emphasis on recent advances in the field. The target audience consists of researchers or students working in AI, robotics, or vision who would like to understand what methods and representations are available for these problems. This lecture summarizes what is and isn't possible to do reliably today, and overviews key concepts that could be employed in systems requiring visual categorization, Mode of access: World Wide Web, System requirements: Adobe Acrobat Reader, Part of: Synthesis digital library of engineering and computer science, Series from website, Includes bibliographical references (p. 133-162), Preface -- Acknowledgments -- Figure credits --, 1. Introduction -- Overview -- Challenges -- The state of the art --, 2. Overview: recognition of specific objects -- Global image representations -- Local feature representations --, 3. Local features: detection and description -- Introduction -- Detection of interest points and regions -- Keypoint localization -- Scale invariant region detection -- Affine covariant region detection -- Orientation normalization -- Summary of local detectors -- Local descriptors -- The SIFT descriptor -- The SURF detector/descriptor -- Concluding remarks --, 4. Matching local features -- Efficient similarity search -- Tree-based algorithms -- Hashing-based algorithms and binary codes -- A rule of thumb for reducing ambiguous matches -- Indexing features with visual vocabularies -- Creating a visual vocabulary -- Vocabulary trees -- Choices in vocabulary formation -- Inverted file indexing -- Concluding remarks --, 5. Geometric verification of…