Journal article
Indexing using a spectral encoding of topological structure
Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition, v 2, pp 491-497
01 Jan 1999
Abstract
In an object recognition system, if the extracted image features are multilevel or multiscale, the indexing structure may take the form of a tree. Such structures are not only common in computer vision, but also appear in linguistics, graphics, computational biology, and a wide range of other domains. In this paper, we develop an indexing mechanism that maps the topological structure of a tree into a low-dimensional vector space. Based on a novel eigenvalue characterization of a tree, this topological signature allows us to efficiently retrieve a small set of candidates from a database of models. To accommodate occlusion and local deformation, local evidence is accumulated in each of the tree's topological subspaces. We demonstrate the approach with a series of indexing experiments in the domain of 2-D object recognition.
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Details
- Title
- Indexing using a spectral encoding of topological structure
- Creators
- Ali Shokoufandeh - Rutgers, The State University of New JerseySven DickinsonKaleem SiddiqiSteven Zucker
- Publication Details
- Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition, v 2, pp 491-497
- Publisher
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Computer Science
- Other Identifier
- 991019203440204721