Книга Front-End Vision and Multi-Scale Image Analysis Bart ter Haar Romeny

Front-End Vision and Multi-Scale Image Analysis

Multi-scale Computer Vision Theory and Applications, written in Mathematica. With online files/update

Автор: Bart ter Haar Romeny
Език: Английски език
Корици: С твърди корици
Издател: Springer Netherlands
Наличност: Външен склад в ограничено количество
Изпращаме след 11-15 дни
178.43 348.98 лв
Many approaches have been proposed to solve the problem of finding the optic flow field of an image...

Информация за книгата

Език
Английски език
Корици
Книга - С твърди корици
Издадена
2003
страници
466
EAN
9781402015038
ISBN
1402015038
Enbook ID
02706140
Издател
Теглоt
890
Размери
155 x 235 x 26

Пълно описание

Many approaches have been proposed to solve the problem of finding the optic flow field of an image sequence. Three major classes of optic flow computation techniques can discriminated (see for a good overview Beauchemin and Barron IBeauchemin19951): gradient based (or differential) methods; phase based (or frequency domain) methods; correlation based (or area) methods; feature point (or sparse data) tracking methods; In this chapter we compute the optic flow as a dense optic flow field with a multi scale differential method. The method, originally proposed by Florack and Nielsen [Florack1998a] is known as the Multiscale Optic Flow Constrain Equation (MOFCE). This is a scale space version of the well known computer vision implementation of the optic flow constraint equation, as originally proposed by Horn and Schunck [Horn1981]. This scale space variation, as usual, consists of the introduction of the aperture of the observation in the process. The application to stereo has been described by Maas et al. [Maas 1995a, Maas 1996a]. Of course, difficulties arise when structure emerges or disappears, such as with occlusion, cloud formation etc. Then knowledge is needed about the processes and objects involved. In this chapter we focus on the scale space approach to the local measurement of optic flow, as we may expect the visual front end to do. 17. 2 Motion detection with pairs of receptive fields As a biologically motivated start, we begin with discussing some neurophysiological findings in the visual system with respect to motion detection.

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