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Computer vision is an interdisciplinary field that deals with how computers can be made to gain high-level understanding from digital images or videos.From the perspective of engineering, it seeks to automate tasks that the human visual system can do.
— This book has a chapter on geometric algorithms. Frank Nielsen. Visual Computing: Graphics, Vision, and Geometry, Charles River Media, 2005. ISBN 1-58450-427-7 — This book combines graphics, vision and geometric computing and targets advanced undergraduates and professionals in game development and graphics. Includes some concise C++ code ...
USC Iris computer vision conference list; Computer vision papers on the web A complete list of papers of the most relevant computer vision conferences. Computer Vision Online News, source code, datasets and job offers related to computer vision. Keith Price's Annotated Computer Vision Bibliography; CVonline Bob Fisher's Compendium of Computer ...
The following is a non-complete list of applications which are studied in computer vision. In this category, the term application should be interpreted as a high level function which solves a problem at a higher level of complexity. Typically, the various technical problems related to an application can be solved and implemented in different ways.
Rick Szeliski (2010), Computer Vision: Algorithms and Applications, Springer. Computational Photography: Methods and Applications (Ed. Rastislav Lukac), CRC Press, 2010. Intelligent Image Processing (John Wiley and Sons book information). Comparametric Equations. GJB-1: Increasing the dynamic range of a digital camera by using the Wyckoff principle
The Caltech 101 data set was used to train and test several computer vision recognition and classification algorithms. The first paper to use Caltech 101 was an incremental Bayesian approach to one-shot learning, [ 4 ] an attempt to classify an object using only a few examples, by building on prior knowledge of other classes.
General scheme of content-based image retrieval. Content-based image retrieval, also known as query by image content and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases (see this survey [1] for a scientific overview of the CBIR field).
Together with Andrew Blake they wrote the book Visual reconstruction published in 1987, which is considered one of the seminal works in the field of computer vision. According to Fitzgibbon (2008) this publication was "one of the first treatments of the energy minimisation approach to include an algorithm (called "graduated non-convexity ...