Paper Info
Title
Top-points as interest points for image matching
Abstract
We consider the use of top-points for object retrieval. These points are based on scale-space and catastrophe theory, and are invariant under gray value scaling and offset as well as scale-Euclidean transformations. The differential properties and noise characteristics of these points are mathematically well understood. It is possible to retrieve the exact location of a top-point from any coarse estimation through a closed-form vector equation which only depends on local derivatives in the estimated point. All these properties make top-points highly suitable as anchor points for invariant matching schemes. By means of a set of repeatability experiments and receiver-operator-curves we demonstrate the performance of top-points and differential invariant features as image descriptors.
Year
DOI
Venue
2006
10.1007/11744023_33
ECCV
Keywords
Field
DocType
interest point,anchor point,closed-form vector equation,image matching,estimated point,differential invariant feature,invariant matching scheme,gray value scaling,coarse estimation,catastrophe theory,exact location,differential property,receiver operator curve,scale space
Computer science,Image processing,Singularity,Scale space,Artificial intelligence,Differential invariant,Computer vision,Topology,Feature vector,Algorithm,Catastrophe theory,Invariant (mathematics),Offset (computer science)
Conference
Volume
ISSN
ISBN
3951
0302-9743
3-540-33832-2
Citations 
PageRank 
References 
14
0.80
12
Authors
4
Name
Order
Citations
PageRank
Bram Platel124521.42
E. Balmachnova2241.75
L. M. J. Florack31212210.47
B. M. Ter Haar Romeny416728.71