3D objects descriptors methods: Overview and trends

Jihad H'Roura (1) , Aissam Bekkari (1) , Driss Mammass (1) , Ali Bouzit (1) , Alamin Mansouri (2) , Michaël Roy (2) , Gaëtan Le Goïc (2)

1 IRF-SIC - Laboratoire Image et Reconnaissance de Formes - Systèmes Intelligents et Communicants
2 Le2i - Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508]

Object recognition or object's category recognition under varying conditions is one of the most astonishing capabilities of human visual system. The scientists in computer vision have been trying for decades to reproduce this ability by implementing algorithms and providing computers with appropriate tools. Hence, several intelligent systems have been proposed. To act in this field, numerous approaches have been proposed. In this paper we present an overview of the current trend in 3D objects recognition and describe some representative state of the art methods, highlighting their limits and complexity.

Mots clés: Three-dimensional displays; Shape; Solid modeling; Computational modeling; Visualization; object recognition; 3D objects recognition; human visual system; computer vision; 3D objects descriptors methods; object category recognition; Recognition; Non-Controlled Indexing; skeleton; Keypoints; intelligent systems

Domaines: Informatique [cs]; Traitement du signal et de l'image [eess.SP]

Jihad H'Roura, Aissam Bekkari, Driss Mammass, Ali Bouzit, Alamin Mansouri, et al.. 3D objects descriptors methods: Overview and trends. 2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), May 2017, Fez, Morocco. ⟨10.1109/ATSIP.2017.8075559⟩. ⟨hal-01858947⟩