Understanding the functions of the skeletal structures of vertebrates in motor control and adaptive strategies for rest posture and locomotion activity is a key issue in several research domains. However, biomechanical expertise reports that current techniques of geometrical prediction of the skeleton structures from 3D external markers present limitations in accuracy due to the fact that flesh and muscles are not rigidly connected to the bones structure. The EVASION research group on computer graphics at INRIA is leading a project on 3D characterization of the relationships between the articulated skeleton of vertebral animals and the deformation of soft tissues (project ANR-Kameleon). This project focuses on the locomotion of small quadruped animals. It is held in cooperation with the National Museum of Natural History in Paris, the biomechanical department of the Rennes University (LPBEM laboratory) and the biomedical department of University Descartes Paris (LNRS laboratory).
We aim to combine skeleton motion data captured with an X-ray videography system and surface deformations measured with a structured light 3D scanner. Standard skinning methods are known to rely on unrealistic approximation of the skin deformation. Using real data collected on animals, the goal of this postdoctoral project is to evaluate the limitations of these methods and investigate a new approach. In particular, methods inspired by machine learning will be considered, such as Lewis et al. in 2000 (“Pose space deformation: A unified approach to shape interpolation and skeleton-driven deformation”, SIGGRAPH’00), Kry et al. in 2002 (“Eigenskin: Real time large deformation character skinning in graphics hardware”, SCA’02) or Mohr et Gleicher in 2003 (“Building Efficient, Accurate Character Skins from Examples”, SIGGRAPH’03). Works by Allen et al. in 2002 have proved the efficiency of the use of static meshes acquired from laser range scanner (“Articulated body deformation from range scan data”, SIGGRAPH’02). This postdoctoral project aims at developing such an approach for the dynamic case of an animal in motion.
Requested skills: Computer Animation, with an emphasis on skinning method and free-form-deformation techniques. Knowledge of Machine Learing will be a plus.
Technical skills: C++ programming, Matlab. Knowledge of Maya software will be a plus.
Language: most exchanges in the project are in English and French. Spoken and written knowledge of English is mandatory. Knowledge of French will be a plus.
Please send a detailed curriculum vitae (maximum 4 pages), a motivation letter and at least one letter of reference from the PhD advisor. Application should be sent by email to lionel.reveret(at)inria.fr or by regular mail to the following address: