Shape geodesics for boundary-based object recognition and retrieval

In this paper we define a distance between shapes based on geodesics in shape space. The proposed distance, robust to outliers, uses shape matching to compare shapes locally. Multiscale analysis is introduced in order to avoid problems of local and global variabilities. The resulting similarity measure is invariant to translation, rotation and scaling independently of constraints or landmarks, but constraints can be added to the approach formulation when needed. An evaluation of the proposed approach is reported for shape classification and retrieval on a complex benchmark shape database. It demonstrates in both cases that previous work is outperformed.

• Publication year

  2009

• Venue

  International Conference on Information Photonics

• Publication date

  2009-11-01

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1109/ICIP.2009.5414454
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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