Probability models for clutter in natural images

Probability models for clutter in natural images

We propose a framework for modeling clutter in natural images. Assuming that: 1) images are made up of 2D (projected) views of 3D (real) objects and 2) certain simplifying conditions hold, we derive an analytical density for natural images. This expression is shown to match well with the observed de...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence 2001-04, Vol.23 (4), p.424-429
Hauptverfasser: Grenander, U., Srivastava, A.
Format: Artikel
Sprache:eng
Schlagworte:
Clutter
Context modeling
Density
Face detection
Image edge detection
Image recognition
Image texture analysis
Intelligence
Mathematical analysis
Object recognition
Pattern analysis
Performance analysis
Pixel
Probability
Shape
Three dimensional
Two dimensional
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Zusammenfassung:We propose a framework for modeling clutter in natural images. Assuming that: 1) images are made up of 2D (projected) views of 3D (real) objects and 2) certain simplifying conditions hold, we derive an analytical density for natural images. This expression is shown to match well with the observed densities (histograms). In addition to deriving multidimensional densities, several extensions are also proposed.
ISSN:0162-8828
1939-3539
DOI:10.1109/34.917579