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Front-End Vision and Multi-Scale Image Analysis

Multi-Scale Computer Vision Theory and Applications, Written in Mathematica

Bart M Haar Romeny
Livre relié | Anglais | Computational Imaging and Vision | n° 27
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Description

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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Contenu

Nombre de pages :
466
Langue:
Anglais
Collection :
Tome:
n° 27

Caractéristiques

EAN:
9781402015038
Date de parution :
30-09-03
Format:
Livre relié
Format numérique:
Genaaid
Dimensions :
164 mm x 242 mm
Poids :
820 g

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