Flexible syntactic matching of curves and its application to automatic hierarchical classification of silhouettes

Yoram Gdalyahu*, Daphna Weinshall

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

202 Scopus citations

Abstract

Curve matching is one instance of the fundamental correspondence problem. Our flexible algorithm is designed to match curves under substantial deformations and arbitrary large scaling and rigid transformations. A syntactic representation is constructed for both curves and an edit transformation which maps one curve to the other is found using dynamic programming. We present extensive experiments where we apply the algorithm to silhouette matching. In these experiments, we examine partial occlusion, viewpoint variation, articulation, and class matching (where silhouettes of similar objects are matched). Based on the qualitative syntactic matching, we define a dissimilarity measure and we compute it for every pair of images in a database of 121 images. We use this experiment to objectively evaluate our algorithm: First, we compare our results to those reported by others. Second, we use the dissimilarity values in order to organize the image database into shape categories. The veridical hierarchical organization stands as evidence to the quality of our matching and similarity estimation.

Original languageAmerican English
Pages (from-to)1312-1328
Number of pages17
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume21
Issue number12
DOIs
StatePublished - 1 Jan 1999

Bibliographical note

Funding Information:
The authors would like to thank Ben Kimia and Daniel Sharvit for the 31 silhouette database and Davi Geiger for the human limbs data. This research is partially funded by the Israeli Ministry of Science.

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