A 3-D Search engine based on Fourier series

Elmustapha Ait Lmaati (1) , Ahmed El Oirrak (1) , Mohamed Daoudi (2, 3) , Driss Aboutajdine (4) , Mohammed Najib Kaddioui (1)

1 Faculté des Sciences Semlalia [Marrakech]
2 LIFL - FOX MIIRE
3 Institut TELECOM/TELECOM Lille1
4 GSCM-LRIT - Laboratoire de Recherche en Informatique et Télécommunications [Rabat]

The size of 3-D data stored around the Web has become bigger. Therefore the development of recognition applications and retrieval systems of 3-D models is important. In this paper we propose a new scheme to measure similarity between 3-D models. The main idea is to reconstruct a 3-D closed curve that represents a 3-D model given by a polygonal mesh, and to extract a signature from this 3-D closed curve using the Fourier series. The proposed descriptor needs continuous principal component analysis (CPCA) to align 3-D models into a canonical position. The feature vectors constructed using this method, named Fourier series descriptor (FSD) are invariants under rigid transformations composed of translation, rotation, flipping and scale; robust to noise and level of detail. A 3-D polygonal mesh model serves as a query for search by shape similarity in a large collection of 3-D models database using an interactive 3-D search engine.

Mots clés: 3-D models; 3-D curve; Polygonal mesh; Fourier series; 3-D search engine

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Elmustapha Ait Lmaati, Ahmed El Oirrak, Mohamed Daoudi, Driss Aboutajdine, Mohammed Najib Kaddioui. A 3-D Search engine based on Fourier series. Computer Vision and Image Understanding, 2010, 114 (1), pp.1-7. ⟨hal-00666579⟩