Linear and Incremental Acquisition of Invariant Shape Models from Image Sequences

Daphna Weinshall, Carlo Tomasi

Research output: Contribution to journalArticlepeer-review

40 Scopus citations


We show how to automatically acquire Euclidian shape representations of objects from noisy image sequences under weak perspective. The proposed method is linear and incremental, requiring no more than pseudoinverse. A nonlinear, but numerically sound preprocessing stage is added to improve the accuracy of the results even further. Experiments show that attention to noise and computational techniques improves the shape results substantially with respect to previous methods proposed for ideal images.

Original languageAmerican English
Pages (from-to)512-517
Number of pages6
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number5
StatePublished - May 1995


  • Euclidean shape
  • Gramian
  • Structure from motion
  • affine coordinates
  • affine shape
  • factorization method
  • linear reconstruction
  • weak perspective


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