Functional Body Mesh Representation,, A Simplified Kinematic Model, Its Inference and Applications

Detection and Classification of Artifact Distortions in Optical Motion Capture Sequences

“…The selection of proper markers to formulate the predictor for each marker according to Equation ( 3) is based on the body's hierarchical structure. For that purpose, we used a body structure as depicted in Figure 5a-a functional body mesh (FBM) [12] for an average human subject, inferred for the typical Vicon marker setup. The FBM hierarchy with the corresponding skeleton is shown in Figure 5b.…”

“…There are two basic assumptions: the rigid body model and a correlation of marker trajectories. A rigid body model was assumed for the functional body mesh (structured point cloud) [12], which we used to represent the subject's body hierarchy. The next assumption stems from the former-it is the fact that the movements of markers are highly correlated and predictable when they are placed on common body parts (e.g., limbs).…”

Gap Reconstruction in Optical Motion Capture Sequences Using Neural Networks

“…The regression/prediction exploits inter-marker correlations between markers placed on the same body parts. Therefore, we employed a functional body mesh structure (FBM) [ 11 ] as a framework to model the kinematic structure of the subject. I Thisan be calculated ad-hoc for any articulated subject or rigid objects, so we do not need a skeleton model.…”

“…Functional body mesh (FBM) is a authors’ original contribution, that forms a framework for marker-wise mocap data processing, which incorporates also the kinematic structure of a represented object. The FBM structure is not given in advance, but it can be inferred based on the articulated object representative motions [ 11 ]. For human actors it resembles standard meshes, but it can be applied for virtually any vertebrates.…”