3D Object Retrieval (3DOR)

As 3D object collections grow in size, due to 3D capture applications and the wider availability of 3D scanners, content-based retrieval grows in importance. 3DOR involves the creation of descriptors that represent the shape and other characteristics of a 3D object in an accurate and compact manner.

A growing number of applications benefit from 3DOR technologies, since they can be cast as inter- or intra-class retrieval problems. These include:

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    3D Biometrics, e.g. 3D face recognition

    For more information on our work with 3D biomestrics,  e.g. 3D face recognition see our Biometrics page.

  • Object reassembly from parts

    Our team worked with object reassembly from parts. An example application for archaeology can be found at our page about the PRESIOUS project.

  • Parts retrieval

    Retrieval of 3D objects for large industrial applications.

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    Object recognition

Our team has been active since the inception of this field.

We have jointly set-up and serve on the Steering Committee of the 3D Object Retrieval workshop series (3DOR), which is usually hosted in conjunction with the Eurographics conference.


We have jointly organised Special Issues in 3D Object Retrieval in journals such as:

Sample publications:

Danelakis A., T. Theoharis, I. Pratikakis & P. Perakis, ‘An Effective Methodology for Dynamic 3D Facial Expression Retrieval’, Pattern Recognition, 52, April 2016, pp. 174-185.

Sfikas K., T. Theoharis, I. Pratikakis, ‘ROSy+: 3D Object Pose Normalization based on PCA and Reflective Object Symmetry with Application in 3D Object Retrieval’, International Journal of Computer Vision (IJCV), 91(3), February 2011, pp. 262-279.

Papadakis P., I. Pratikakis, T. Theoharis and S. Perantonis, ‘PANORAMA: A 3D Shape Descriptor based on Panoramic Views for Unsupervised 3D Object Retrieval’, International Journal of Computer Vision (IJCV), 89(2/3), September 2010, pp. 177-192.