Feature-level and descriptor-level information fusion for density-based 3D shape descriptors. Akguel, C. B., Sankurl, B., Yemez, Y., & Schmitt, F. In 2007 IEEE 15TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS, VOLS 1-3, pages 334-337, 2007. IEEE. IEEE 15th Signal Processing and Communications Applications Conference, Eskisehir, TURKEY, JUN 11-13, 2007
abstract   bibtex   
We address the 3D object retrieval problem using density-based shape descriptors. We explore first and second order local surface features and their multivariate combinations in the density estimation framework. We also experiment with descriptor level information fusion. The results, obtained using two different databases, Princeton Shape Benchmark and Sculpteur, show that, boosted with both feature level and descriptor level information fusion, the density-based shape description framework enables effective and efficient 3D object retrieval.
@inproceedings{ ISI:000252924600084,
Author = {Akguel, Ceyhun Burak and Sankurl, Buelent and Yemez, Yuecel and Schmitt,
   Francis},
Book-Group-Author = {{IEEE}},
Title = {{Feature-level and descriptor-level information fusion for density-based
   3D shape descriptors}},
Booktitle = {{2007 IEEE 15TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS, VOLS
   1-3}},
Year = {{2007}},
Pages = {{334-337}},
Note = {{IEEE 15th Signal Processing and Communications Applications Conference,
   Eskisehir, TURKEY, JUN 11-13, 2007}},
Organization = {{IEEE}},
Abstract = {{We address the 3D object retrieval problem using density-based shape
   descriptors. We explore first and second order local surface features
   and their multivariate combinations in the density estimation framework.
   We also experiment with descriptor level information fusion. The
   results, obtained using two different databases, Princeton Shape
   Benchmark and Sculpteur, show that, boosted with both feature level and
   descriptor level information fusion, the density-based shape description
   framework enables effective and efficient 3D object retrieval.}},
ISBN = {{978-1-4244-0719-4}},
Unique-ID = {{ISI:000252924600084}},
}

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