Recognizing Planar Objects in 3-D Space

Nirwan Ansari, Edward J. Delp

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Object recognition is a major theme in computer vision. In this paper, we present a method of recognizing planar objects in 3-D space from a single image. Objects in a scene may be occluded, and the orientation of the objects is arbitrary. We represent each object by its dominant points, and pose the recognition problem as a dominant-point matching problem. We introduce a measure, known as sphericity, derived from an affine transform to indicate the quality of match among dominant points. A clustering algorithm, probe-and-block, is used to guide the matching. We use a least squares fit among dominant points to estimate object location in the scene. A heuristic measure is finally computed to verify the match.

Original languageEnglish (US)
Pages (from-to)127-138
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume1197
DOIs
StatePublished - Feb 1 1990

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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