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DSSCV Résumé de rapport

Project ID: IST-2001-35443
Financé au titre de: FP5-IST
Pays: Netherlands

Report on structural search by MSSTs and performance evaluation report on object matching

We have addressed the nontrivial task of finding a fiducial object, captured by a digital image ("query image"), in another image, or database of such images, consisting of complex configurations of various objects ("scene image"). The requirements posed to this object retrieval or structural search problem include robustness under various degrading factors, notably noise, occlusion, and invariance under similarity transformations, i.e. relative translation, rotation, and scaling of reference frames of scene object relative to query object. In addition the algorithm should be operationally defined and mathematically rigorous.

Elaborating on pioneering heuristics by Lowe, further developed by Mikolajczyk, and Schmid (which has led to promising results, but lacking mathematical underpinning) we have realized a prototype object retrieval algorithm that combines the strengths of Lowe's heuristics and mathematical rigor. This has the benefit that the object retrieval problem has been cast into a well-understood conceptual framework and a transparent algorithm.

A performance comparison shows that our object retrieval algorithm competes with state-of-the-art heuristic algorithms despite its very generic nature (no application specific tuning or hidden parameters have been incorporated). As such our framework is quite susceptible to future improvements by the scientific community. The ultimate goal of a fully operational generic object retrieval algorithm for structural search in image databases (e.g. object google, forensic research or comparisons of clinically similar cases) has thus come within closer reach. However, several weaknesses will have to be overcome; in particular computational efficiency will have to be improved, and deviations from similarity transformations between query object and matching scene object will have to be accounted for.

Informations connexes


Luc FLORACK, (Associate Professor)
Tél.: +31-40-2475377
Fax: +31-40-2472740