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Discrete Representation of Top Points via Scale Space Tessellation
Book chapter   Peer reviewed

Discrete Representation of Top Points via Scale Space Tessellation

B Platel, M. Fatih Demirci, A Shokoufandeh, L. M. J Florack, F. M. W Kanters, B. M ter Haar Romeny and S. J Dickinson
Scale Space and PDE Methods in Computer Vision
2005

Abstract

Coarse Scale Critical Path Delaunay Triangulation Directed Acyclic Graph Scale Space
In previous work, singular points (or top points) in the scale space representation of generic images have proven valuable for image matching. In this paper, we propose a construction that encodes the scale space description of top points in the form of a directed acyclic graph. This representation allows us to utilize graph matching algorithms for comparing images represented in terms of top point configurations instead of using solely the top points and their features in a point matching algorithm, as was done previously. The nodes of the graph represent the critical paths together with their top points. The edge set will capture the neighborhood distribution of vertices in scale space, and is constructed through a Delaunay triangulation scheme. We also will present a many-to-many matching algorithm for comparing such graph-based representations. This algorithm is based on a metric-tree representation of labelled graphs and their low-distortion embeddings into normed vector spaces via spherical encoding. This is a two-step transformation that reduces the matching problem to that of computing a distribution-based distance measure between two such embeddings. To evaluate the quality of our representation, two sets of experiments are considered. First, the stability of this representation under Gaussian noise of increasing magnitude is examined. In the second set of experiments, a series of recognition experiments is run on a small face database.

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Web of Science research areas
Computer Science, Artificial Intelligence
Computer Science, Theory & Methods
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