Perceptual organization and visual recognition

  title={Perceptual organization and visual recognition},
  author={David G. Lowe},
  • D. Lowe
  • Published 14 February 2012
  • Computer Science
A computational model is presented for the visual recognition of three-dimensional objects based upon their spatial correspondence with two-dimensional features in an image. A number of components of this model are developed in further detail and implemented as computer algorithms. At the highest level, a verification process has been developed which can determine exact values of viewpoint and object parameters from hypothesized matches between three-dimensional object features and two… 

Three-Dimensional Object Recognition from Single Two-Dimensional Images

  • D. Lowe
  • Computer Science
    Artif. Intell.
  • 1987

Geometric Aspects of Visual Object Recognition

A recognition algorithm (RAST) that works efficiently even when no correspondence or grouping information is given; that is, it works in the presence of large amounts of clutter and with very primitive features form the basis for a simple, efficient, and robust approach to the geometric aspects of 3D object recognition from 2D image.

A network that learns to recognize three-dimensional objects

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The model was not conceived to explain brain functions, but it does cohere with evidence about the functions of neurons in V1 and V2, such as responses to coarse or incomplete patterns and to scale and translation invariance in IT.

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In this review current theories of the visual perception of three-dimensional form are introduced. Starting with a brief overview of low-level visual processes, which contribute to the recognition of

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  • R. BergevinM. Levine
  • Computer Science
    [1990] Proceedings. 10th International Conference on Pattern Recognition
  • 1990
The authors describe the geometrical criteria which define viewpoint-invariant features to be extracted from 2-D line drawings of 3-D objects. They also discuss the extraction of these features,

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