This book presents a comprehensive treatise on Riemannian geometric computations and related statistical inferences in several computer vision problems. This edited volume includes chapter contributions from leading figures in the field of computer vision who are applying Riemannian geometric approaches in problems such as face recognition, activity recognition, object detection, biomedical image analysis, and structure-from-motion. Some of the mathematical entities that necessitate a geometric analysis include rotation matrices (e.g. in modeling camera motion), stick figures (e.g. for activity recognition), subspace comparisons (e.g. in face recognition), symmetric positive-definite matrices (e.g. in diffusion tensor imaging), and function-spaces (e.g. in studying shapes of closed contours).
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Pavan Turaga is an Assistant Professor at Arizona State University Anuj Srivastava is a Professor at Florida State University
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Descripción Springer, 2016. Paperback. Estado de conservación: NEW. 9783319360959 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Nº de ref. de la librería HTANDREE01397643
Descripción Springer, 2017. Estado de conservación: New. This item is printed on demand for shipment within 3 working days. Nº de ref. de la librería LP9783319360959