Reinhard Klette's Concise Computer Vision: An Introduction into Theory and PDF

By Reinhard Klette

ISBN-10: 1447163206

ISBN-13: 9781447163206

Many textbooks on computing device imaginative and prescient could be unwieldy and intimidating of their assurance of this wide self-discipline. This textbook addresses the necessity for a concise review of the basics of this field.

Concise desktop imaginative and prescient presents an available basic creation to the basic issues in computing device imaginative and prescient, highlighting the position of significant algorithms and mathematical thoughts. Classroom-tested programming workouts and evaluation questions also are provided on the finish of every chapter.

Topics and features:

* offers an creation to the fundamental notation and mathematical thoughts for describing a picture, and the major options for mapping a picture into an image
* Explains the topologic and geometric fundamentals for analysing picture areas and distributions of photo values, and discusses settling on styles in an image
* Introduces optic circulate for representing dense movement, and such issues in sparse movement research as keypoint detection and descriptor definition, and have monitoring utilizing the Kalman filter
* Describes unique techniques for snapshot binarization and segmentation of nonetheless photographs or video frames
* Examines the 3 uncomplicated elements of a working laptop or computer imaginative and prescient approach, particularly digicam geometry and photometry, coordinate platforms, and digicam calibration
* reports varied options for vision-based 3D form reconstruction, together with using based lighting fixtures, stereo imaginative and prescient, and shading-based form understanding
* features a dialogue of stereo matchers, and the phase-congruency version for picture features
* provides an advent into category and studying, with an in depth description of easy AdaBoost and using random forests

This concise and straightforward to learn textbook/reference is perfect for an introductory path at 3rd- or fourth-year point in an undergraduate machine technological know-how or engineering programme.

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Extra resources for Concise Computer Vision: An Introduction into Theory and Algorithms (Undergraduate Topics in Computer Science)

Sample text

To address the issue of varying albedo, a direct 2D-to-2D approach was proposed with the assumption that front-view faces are symmetric and the use of a generic 3D model [108]. Recall that a prototype image Ip is a frontal-view with Ps = 0, Qs = 0. Substituting this into Equation 9, we have Ip [x, y] = ρ √ 1 2 2 . 1+p +q K (I[x, y] + I[−x, y]). This equation Simple manipulation yields Ip [x, y] = 2(1+qQ s) directly relates the prototype image Ip to I[x, y] + I[x, −y] which is already available.

Hence infrared imagery, which is insensitive to illumination variation, can serve as an alternative source of information for detection and recognition. However, the inferior resolution of IR images is a drawback. Further, though IR imagery is insensitive to changes in illumination, it is sensitive to changes in temperature. Three face-recognition algorithms were applied to both visible and IR images. The recognition results on 101 subjects suggested that visible and IR imagery perform similarly across algorithms, and that by fusing IR and visible imagery one can enhance the performance compared to using either one.

A face tracking system was used in [150] to estimate the pose of the face. This system used a graph representation with about 20–40 nodes/landmarks to model the face. Knowledge about faces is used to find the landmarks in the first frame. Two tracking systems described in [120, 155] model faces completely with texture and geometry. Both systems use generic 3D models and SfM to recover the face structure. [120] tracks fixed feature points (eyes, nose tip), while [155] tracks only points with high Hessian values.

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Concise Computer Vision: An Introduction into Theory and Algorithms (Undergraduate Topics in Computer Science) by Reinhard Klette

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