Invalidity dossier
US 6496184
Method for inferring scenes from test images and training data using probability propagation in a markov network
Current assignee: Mitsubishi Electric Research Laboratories Inc
Added 9/23/2026, 11:40:31 PM
Active provider: DeepSeek · deepseek-flash
Patent summary
Title, assignee, inventors, filing/issue dates, abstract, and a plain-language overview of the claims.
Patent Overview: US 6,496,184 B1
Title: Method for inferring scenes from test images and training data using probability propagation in a markov network
Patent number: US 6,496,184 B1
Application number: US09/335,943
Inventors: William T. Freeman; Egon C. Pasztor; Baback Moghaddam
Original assignee: Mitsubishi Electric Research Laboratories Inc
Priority date: 1998-11-30
Filing date: 1999-06-18
Publication/grant date: 2002-12-17
Status listed: Expired – Fee Related; anticipated expiration 2018-11-30
Purpose. The invention addresses the general problem of inferring overall characteristics of a real-world signal from isolated or degraded samples—for example, estimating object velocities in video, recovering 3-D structure from 2-D images, or recovering high-resolution details from low-resolution signals. The described method aims to infer a scene from a test image.
Plain-language scope. During a training phase, labeled images and corresponding scenes are acquired (by synthesis or measurement) and partitioned into image patches and scene patches. Each patch is represented as a low-dimensional vector (the excerpt gives examples of five-dimensional scene vectors and seven-dimensional image vectors), with each vector modeled as a node in a network, preferably a Markov network; edges model statistical dependencies between nodes. In the inference phase, an unknown test image is partitioned into test image patches represented as test image vectors. Candidate scene vectors corresponding to those test image vectors are located in the training data, compatibility matrices for candidate scene vectors at neighboring network nodes are determined, and probabilities are propagated in the network until a predetermined termination condition (convergence or a fixed number of iterations) is reached, thereby inferring the scene.
What the excerpt does not establish. It does not establish litigation, ownership transfers beyond the listed assignments, validity, or prior art beyond the brief mentions of quad-tree optical flow and brightness constancy. It also omits full claim language, so the exact legal scope cannot be confirmed from this excerpt.
Generated 10/1/2026, 9:32:34 PM
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Assignment history
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Prior art
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