Computer Vision: A Reference Guide by Katsushi Ikeuchi

By Katsushi Ikeuchi

This entire reference presents easy accessibility to appropriate info on all facets of desktop imaginative and prescient. An A-Z structure of over 240 entries bargains a various variety of issues for these looking access into any point in the wide box of computing device imaginative and prescient. Over 2 hundred Authors from either and academia contributed to this volume.

Each access contains synonyms, a definition and dialogue of the subject, and a strong bibliography. vast cross-references to different entries aid effective, common searches for fast entry to correct info. Entries have been peer-reviewed by means of a amazing foreign advisory board, either scientifically and geographically varied, making sure balanced assurance. Over 3700 bibliographic references for extra interpreting let deeper exploration into any of the themes covered.

The content material of Computer imaginative and prescient: A Reference Guide is expository and educational, making the booklet a pragmatic source for college students who're contemplating coming into the sphere, in addition to pros in different fields who have to entry this very important info yet would possibly not have the time to paintings their method via a whole textual content on their subject of interest.

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By Katsushi Ikeuchi

This entire reference presents easy accessibility to appropriate info on all facets of desktop imaginative and prescient. An A-Z structure of over 240 entries bargains a various variety of issues for these looking access into any point in the wide box of computing device imaginative and prescient. Over 2 hundred Authors from either and academia contributed to this volume.

Each access contains synonyms, a definition and dialogue of the subject, and a strong bibliography. vast cross-references to different entries aid effective, common searches for fast entry to correct info. Entries have been peer-reviewed by means of a amazing foreign advisory board, either scientifically and geographically varied, making sure balanced assurance. Over 3700 bibliographic references for extra interpreting let deeper exploration into any of the themes covered.

The content material of Computer imaginative and prescient: A Reference Guide is expository and educational, making the booklet a pragmatic source for college students who're contemplating coming into the sphere, in addition to pros in different fields who have to entry this very important info yet would possibly not have the time to paintings their method via a whole textual content on their subject of interest.

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Extra resources for Computer Vision: A Reference Guide

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Changes in observer viewpoint are used in active vision systems for a number of purposes. Some of the more important uses are: – Tracking a moving object to keep it in the field of view of the sensor – Searching for a specific item in the observer’s environment – Inducing scene-dependent optical flow to aid in the extraction of 3D structure of objects and scenes – Avoiding “accidental” or nongeneric viewpoints, which can result in sensor-saturating specularities or information-hiding occlusions – Minimizing sensor noise and maximizing novel information content – Increasing the dynamic range of the sensor, through adjustment of parameters such as sensor sensitivity, aperture, and focus – Mapping the observer’s environment Theory LowLevel Camera Motion Control Systems Most robotic active vision control systems act mainly to produce either smooth pursuit motions or rapid saccadic motions.

Pont Industrial Design Engineering, Delft University of Technology, Delft, The Netherlands Emmanuel Prados INRIA Rhône-Alpes, Montbonnot, France Jerry L. Prince Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA Srikumar Ramalingam Mitsubishi Electric Research Laboratories, Cambridge, MA, USA Rajeev Ramanath DLP R TX, USA Products, Texas Instruments Incorporated, Plano, Dikpal Reddy Nvidia Research, Santa Clara, CA, USA Xiaofeng Ren Intel Science and Technology Center for Pervasive Computing, Intel Labs, Seattle, WA, USA Xuejun Ren School of Engineering Liverpool John Moores University, Liverpool, UK xxxii Szymon Rusinkiewicz Department of Computer Science, Princeton University, Princeton, NJ, USA Aswin C.

There are two commonly used STIP extraction techniques. One extends Harris corner detection and automatic scale selection in 2D space to 3D space and time [6] and the other is based on a pair of one-dimensional (1D) Gabor filters applied temporally and spatially [7]. Recently, another STIP detector has been proposed by decomposing an image sequence into spatial components and motion components using nonnegative matrix factorization and detecting STIPs in 2D spatial and 1D motion space using difference of Gaussian (DoG) detectors [8].

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