Patent
Method for inferring scenes from test images and training data using probability propagation in a markov network
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TLDR
In this article, a method is proposed to infer a scene from a test image using a set of images and corresponding scenes, where each of the images and scenes are partitioned respectively into a plurality of image patches and scene patches, and probabilities of the compatibility matrices are propagated in the network until convergence.Abstract:
A method infers a scene from a test image During a training phase, a plurality of images and corresponding scenes are acquired Each of the images and corresponding scenes are partitioned respectively into a plurality of image patches and scene patches Each image patch is represented as an image vector, and each scene patch is represented as a scene vector The image vectors and scene vectors are modeled as a network During an inference phase, the test image is acquired The test image is partitioned into a plurality of test image patches Each test image patch is represented as a test image vector Candidate scene vectors corresponding to the test image vectors are located in the network Compatibility matrices for the candidate scene vectors are determined, and probabilities of the compatibility matrices are propagated in the network until convergence to infer the scene from the test imageread more
Citations
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Patent
Aerial roof estimation systems and methods
Chris Pershing,David P. Carlson +1 more
TL;DR: In this article, the authors describe methods and systems for roof estimation, which generate and provide roof estimate reports annotated with indications of the size, geometry, pitch and/or orientation of the roof sections of a building.
Patent
Concurrent display systems and methods for aerial roof estimation
TL;DR: In this paper, a user interface for roof estimation is described, which can be manipulated by an operator to perform at least some of the functions of roof model generation, including image registration, image lean correction, roof section pitch determination, wire frame model construction, and/or roof model review.
Patent
Pitch determination systems and methods for aerial roof estimation
TL;DR: In this paper, a user interface for roof estimation is described, which can be manipulated by an operator to perform at least some of the functions of roof model generation, such as image registration, image lean correction, roof section pitch determination, wire frame model construction, and/or roof model review.
Patent
System and Process for Roof Measurement Using Aerial Imagery
TL;DR: In this article, a first layer and a second layer, in computer memory and substantially overlapping at least a segment of line from the first layer with at least another segment from the second layer are shown.
Patent
System and method for construction estimation using aerial images
James Edward Loveland,Jeffrey C. Taylor,Jeffery D. Lewis,Bradley McKay Childs,Corey David Reed,Jared William Robertson +5 more
TL;DR: In this paper, a system and method for construction estimation using aerial images is presented, which allows users to generate two-dimensional and three-dimensional models of the roof by automatically delineating various roof features, and generates a report including information about the roof of the building.
References
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Patent
Method and apparatus for classifying and identifying images
TL;DR: In this paper, an image processing system utilizes a class model defined by one or more relative relationships between a plurality of image patches, which describe the overall organization of images within an image class.
Patent
Image mosaic construction system and apparatus with patch-based alignment, global block adjustment and pair-wise motion-based local warping
TL;DR: In this article, a patch-based alignment of the set of overlapping images is performed to produce a set of warped images, and then a block adjustment of the warped image is performed.
Proceedings ArticleDOI
A probabilistic framework for perceptual grouping of features for human face detection
Kin Choong Yow,Roberto Cipolla +1 more
TL;DR: A face detection framework that groups image features into meaningful entities-using perceptual organization, assigns probabilities to each of them, and reinforce there probabilities using Bayesian reasoning techniques is proposed.
Proceedings Article
Learning to Estimate Scenes from Images
TL;DR: From synthetic data, the relationship between image and scene patches is modeled, and between a scene patch and neighboring scene patches, and this yields an efficient method to form low-level scene interpretations.
Patent
System for identifying objects and features in an image
TL;DR: In this paper, the use of the fundamental concept of color perception and multi-level resolution is used to perform scene segmentation and object/feature extraction in the context of self-determining and self-calibration modes.