État de l'art des méthodes de segmentation de séquences de maillages et proposition d'une classification

National audienceLes séquences de maillages représentent un nouveau type de contenu, de plus en plus utilisé dans le domaine du multimédia. Les applications que sont la compression, l'indexation, etc. s'appliquent désormais à ce type de données. Compte-tenu de la taille très importante de ces données, une segmentation préalable est souvent nécessaire. Dans cet article, nous proposons dans un premier temps une formalisation des notions de "séquence de maillages" et de "segmentation de séquence de maillages". Puis nous présentons un état de l'art des différentes méthodes de segmentation de séquences de maillages. Finalement, nous présentons différentes applications possibles de la segmentation de séquences de maillages

Towards key-frame extraction methods for 3D video: a review

The increasing rate of creation and use of 3D video content leads to a pressing need for methods capable of lowering the cost of 3D video searching, browsing and indexing operations, with improved content selection performance. Video summarisation methods specifically tailored for 3D video content fulfil these requirements. This paper presents a review of the state-of-the-art of a crucial component of 3D video summarisation algorithms: the key-frame extraction methods. The methods reviewed cover 3D video key-frame extraction as well as shot boundary detection methods specific for use in 3D video. The performance metrics used to evaluate the key-frame extraction methods and the summaries derived from those key-frames are presented and discussed. The applications of these methods are also presented and discussed, followed by an exposition about current research challenges on 3D video summarisation methods

Motion Segmentation and Retrieval for 3D Video Based on Modified Shape Distribution

<p/> <p>A similar motion search and retrieval system for 3D video are presented based on a modified shape distribution algorithm. 3D video is a sequence of 3D models made for a real-world object. In the present work, three fundamental functions for efficient retrieval have been developed: feature extraction, motion segmentation, and similarity evaluation. Stable-shape feature representation of 3D models has been realized by a modified shape distribution algorithm. Motion segmentation has been conducted by analyzing the degree of motion using the extracted feature vectors. Then, similar motion retrieval has been achieved employing the dynamic programming algorithm in the feature vector space. The experimental results using 3D video sequences of dances have demonstrated very promising results for motion segmentation and retrieval.</p