US6263103B1
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Estimating scenes using statistical properties of images and scenes
Assignee: Mitsubishi Electric Research Laboratories Inc
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Filing: 1998-11-30
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Granted: 2001-07-17
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Expires: 2018-11-30
Abstract
Abstract A method for estimating scenes from images generates a plurality of scenes and renders an image for each scene. The scenes and corresponding images are partitioned into patches. Each patch is quantitized as a vector and probability density function is fitted to each vector. The patches and probability densities are organized as a Markov network where local probability information is propagated to neighboring nodes. After propagation, the probability density at each node is used to estimate the scene.
Inventors
- 👤 William T. Freeman
- 👤 Egon C. Pasztor
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 13:47
CPC Classifications
G; G06; G06T; G06T7/00; G06T7/40; G06T7/41; G06V; G06V20/00
Claims Analysis
Total Claims: 12
Claim 1
Independent Claim
77 words
A method for estimating scenes from images, comprising the steps of: generating a plurality of scenes and rendering an image for each scene; partitioning each scene and corresponding image into patches; quantifying each patch as a vector and modeling a probability density to each vector; representing the patches and probability densities as a network; iteratively propagating local probability information to neighboring nodes of the network; and reading the probability density at each node to estimate the scene.
Claim 2
Independent Claim
77 words
A method for estimating scenes from images, comprising the steps of: generating a plurality of scenes and rendering an image for each scene; partitioning each scene and corresponding image into patches; quantifying each patch as a vector and modeling a probability density to each vector; representing the patches and probability densities as a network; iteratively propagating local probability information to neighboring nodes of the network; and reading the probability density at each node to estimate the scene.
Claim 3
Dependent Claim
13 words
The method of claim 1 wherein the scenes and images are synthetically generated.
Claim 4
Dependent Claim
15 words
The method of claim 2 wherein the scenes and images are generated by computer graphics.
Claim 5
Dependent Claim
13 words
The method of claim 1 wherein the scenes and images are randomly generated.
Claim 6
Dependent Claim
12 words
The method of claim 1 wherein the patches can have multiple sizes.
Claim 7
Dependent Claim
11 words
The method of claim 1 wherein the patches are redundantly overlaid.
Claim 8
Dependent Claim
20 words
The method of claim 1 wherein the patches are organized as a gaussian pyramid having a plurality of resolution levels.
Claim 9
Dependent Claim
14 words
The method of claim 1 wherein the vectors are determined by principle components analysis.
Claim 10
Dependent Claim
12 words
The method of claim 1 wherein the network is a Markov chain.
Claim 11
Dependent Claim
29 words
The method of claim 9 wherein nodes of the network represent the patches and the associated probability densities, and edges connecting the nodes represent statistical dependencies between the nodes.
Claim 12
Dependent Claim
20 words
The method of claim 10 wherein local probabilities are propagated by factorizing joint probabilities of neighboring nodes of the network.
References Cited (Backward Citations)
USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2004-07-16 | 2005-01-15 | 2005-07-17 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2008-07-16 | 2009-01-15 | 2009-07-17 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2012-07-16 | 2013-01-15 | 2013-07-17 | $7700.00 | Window Closed / Lapsed |