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  • 1
    E-Resource
    E-Resource
    Berlin [u.a.] : Springer
    Associated volumes
    Keywords: Maschinelles Sehen ; Konferenzschrift 1996 ; Maschinelles Sehen
    Type of Medium: Electronic Resource
    Pages: 1 Online-Ressource
    Series Statement: Lecture notes in computer science
    RVK:
    Language: Undetermined
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  • 2
    Online Resource
    Online Resource
    Berlin [u.a.] : Springer
    Part of " Computer vision - ECCV '96"
    Part of " Lecture notes in computer science"
    Keywords: Maschinelles Sehen ; Maschinelles Sehen
    Type of Medium: Online Resource
    Pages: 1 Online-Ressource (XIX, 723 S. , Ill., graph. Darst.)
    ISBN: 3540611231
    Series Statement: Lecture notes in computer science 1065
    Language: Undetermined
    Location Call Number Limitation Availability
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  • 3
    Online Resource
    Online Resource
    Berlin [u.a.] : Springer
    Part of " Computer vision - ECCV '96"
    Part of " Lecture notes in computer science"
    Keywords: Maschinelles Sehen ; Maschinelles Sehen
    Type of Medium: Online Resource
    Pages: 1 Online-Ressource (XIX, 725 S. , Ill., graph. Darst.)
    ISBN: 3540611223
    Series Statement: Lecture notes in computer science 1064
    Language: Undetermined
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    ISSN: 1573-1405
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This paper describes the combination of several novel algorithms into a system that obtains visual motion from a sequence of images and uses it to recover a three-dimensional description of the motion and geometry of the scene in terms of moving extended straight edges. The system goes on to recognize the recovered geometry as an object from a database of wireframe models, a stage that also resolves the depth/speed scaling ambiguity inherent in visual motion processing, resulting in absolute depth and motion recovery. The processing sequence is demonstrated on imagery from a well-carpentered CSG model and on natural imagery of simple polyhedral objects.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    ISSN: 1573-1405
    Keywords: colour ; statistics ; statistical modeling ; segmentation ; tracking ; active region models ; snakes ; image processing ; computer vision ; physics-based vision
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract In this paper we investigate how best to model naturally arising distributions of colour camera data. It has become standard to model single mode distributions of colour data by ignoring the intensity component and constructing a Gaussian model of the chromaticity. This approach is appealing, because the intensity of data can change arbitrarily due to shadowing and shading, whereas the chromaticity is more robust to these effects. However, it is unclear how best to construct such a model, since there are many domains in which the chromaticity can be represented. Furthermore, the applicability of this kind of model is questionable in all but the most basic lighting environments. We begin with a review of the reflection processes that give rise to distributions of colour data. Several candidate models are then presented; some are from the existing literature and some are novel. Properties of the different models are compared analytically and the models are empirically compared within a region tracking application over two separate sets of data. Results show that chromaticity based models perform well in constrained environments where the physical model upon which they are based applies. It is further found that models based on spherical representations of the chromaticity data provide better performance than those based on more common planar representations, such as the chromaticity plane or the normalised colour space. In less constrained environments, however, such as daylight, chromaticity based models do not perform well, because of the effects of additional illumination components, which violate the physical model upon which they are based.
    Type of Medium: Electronic Resource
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