Multi-resolution recognition of 3D objects based on visual resolution limits

Huimin Ma, Tiantian Huang, Yanzhi Wang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


This paper presents a multi-resolution recognition method for 3D objects, based on the human visual model. In the first part of this paper, we propose a new visual resolution limit (VRL) calculation method that considers lens size, the scale of imaging cells and the distance, orientation and velocity of the object. In addition, we simplify 3D models with a novel mesh simplification method based on edge collapse, which controls the simplification degree with VRL. After applying viewpoint space partitioning to the simplified models at different resolutions, we develop a multi-resolution aspect graph library indexed by observation distance. Finally, we propose a 3D object recognition method based on multi-resolution aspect graphs and implement a real-time gradual multi-resolution recognition system that imitates human vision. We design and execute a set of experiments based on plane, car and ship models. Our results demonstrate that our recognition method is effective.

Original languageEnglish (US)
Pages (from-to)259-266
Number of pages8
JournalPattern Recognition Letters
Issue number3
StatePublished - Feb 1 2010
Externally publishedYes


  • 3D object recognition
  • Mesh simplification
  • Multi-resolution aspect graph
  • Visual resolution limit (VRL)

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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