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Title: System and method for extracting dominant orientations from a scene

In one embodiment, a method of identifying the dominant orientations of a scene comprises representing a scene as a plurality of directional vectors. The scene may comprise a three-dimensional representation of a scene, and the plurality of directional vectors may comprise a plurality of surface normals. The method further comprises determining, based on the plurality of directional vectors, a plurality of orientations describing the scene. The determined plurality of orientations explains the directionality of the plurality of directional vectors. In certain embodiments, the plurality of orientations may have independent axes of rotation. The plurality of orientations may be determined by representing the plurality of directional vectors as lying on a mathematical representation of a sphere, and inferring the parameters of a statistical model to adapt the plurality of orientations to explain the positioning of the plurality of directional vectors lying on the mathematical representation of the sphere.
Inventors:
; ; ; ;
Issue Date:
OSTI Identifier:
1360774
Assignee:
Massachusetts Institute of Technology PNNL
Patent Number(s):
9,665,791
Application Number:
14/678,585
Contract Number:
FC02-99ER54512; FA8650-11-1-7154
Resource Relation:
Patent File Date: 2015 Apr 03
Research Org:
Massachusetts Institute of Technology, Cambridge, MA (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Other works cited in this record:

Method and apparatus for enhancing discrete pixel images
patent, March 2001

Joint component framework for modeling complex joint behavior
patent, February 2008

Method and apparatus for determining item orientation
patent, July 2012

Methods and systems for 3D shape retrieval
patent, December 2013

Vanishing points and three-dimensional lines from omni-directional video
journal, October 2003
  • Bosse, Michael; Rikoski, Richard; Leonard, John
  • The Visual Computer, Vol. 19, Issue 6, p. 417-430
  • DOI: 10.1007/s00371-003-0205-3

21/2 D Scene Reconstruction of Indoor Scenes from Single RGB-D Images
book, January 2013

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