5 research outputs found
Motion Capture Data Completion via Truncated Nuclear Norm Regularization
The objective of motion capture (mocap) data completion is to recover missing measurement of the body markers from mocap. It becomes increasingly challenging as the missing ratio and duration of mocap data grow. Traditional approaches usually recast this problem as a low-rank matrix approximation problem based on the nuclear norm. However, the nuclear norm defined as the sum of all the singular values of a matrix is not a good approximation to the rank of mocap data. This paper proposes a novel approach to solve mocap data completion problem by adopting a new matrix norm, called truncated nuclear norm. An efficient iterative algorithm is designed to solve this problem based on the augmented Lagrange multiplier. The convergence of the proposed method is proved mathematically under mild conditions. To demonstrate the effectiveness of the proposed method, various comparative experiments are performed on synthetic data and mocap data. Compared to other methods, the proposed method is more efficient and accurate
Spatio-temporal reconstruction for 3D motion recovery
—This paper addresses the challenge of 3D motion
recovery by exploiting the spatio-temporal correlations of corrupted 3D skeleton sequences. We propose a new 3D motion recovery method using spatio-temporal reconstruction, which uses
joint low-rank and sparse priors to exploit temporal correlation
and an isometric constraint for spatial correlation. The proposed
model is formulated as a constrained optimization problem,
which is efficiently solved by the augmented Lagrangian method
with a Gauss-Newton solver for the subproblem of isometric
optimization. Experimental results on the CMU motion capture
dataset, Edinburgh dataset and two Kinect datasets demonstrate
that the proposed approach achieves better motion recovery
than state-of-the-art methods. The proposed method is applicable
to Kinect-like skeleton tracking devices and pose estimation
methods that cannot provide accurate estimation of complex
motions, especially in the presence of occlusion