A Fully-Automatic Gap Filling Approach for Motion Capture Trajectories

Missing marker information is a common problem in Motion Capture (MoCap) systems. Commercial MoCap software provides several methods for reconstructing incomplete marker trajectories; however, these methods still rely on manual intervention. Current alternatives proposed in the literature still present drawbacks that prevent their widespread adoption. The lack of fully automated and universal solutions for gap filling is still a reality. We propose an automatic frame-wise gap filling routine that simultaneously explores restrictions between markers’ distance and markers’ dynamics in a least-squares minimization problem. This algorithm constitutes the main contribution of our work by simultaneously overcoming several limitations of previous methods that include not requiring manual intervention, prior training or training data; not requiring information about the skeleton or a dedicated calibration trial and by being able to reconstruct all gaps, even if these are located in the initial and final frames of a trajectory. We tested our approach in a set of artificially generated gaps, using the full body marker set, and compared the results with three methods available in commercial MoCap software: spline, pattern and rigid body fill. Our method achieved the best overall performance, presenting lower reconstruction errors in all tested conditions.

Using a Gauge Block for Derivation of Parameters of Four Laser Triangulation Sensors in a Local Coordinate System

The paper discusses the derivation of an accurate coordinate measuring system consisting of two, three, or four sensors based on the records of four fixed laser triangulation sensors done for a gauge block in movement. Three-dimensional case is considered. In the simulations, using a set of distances quadruplets, parameters of sensors in a local sensors coordinate system are determined through a least squares minimization process using the Differential Evolution approach. The influence of the measurement and rounding inaccuracy on the identification accuracy using numerical simulation methods are assessed.

A least-squares minimization approach to interpret gravity anomalies caused by a 2D thick, vertically faulted slab

We present a least-squares minimization approach to estimate simultaneously the depth to and thickness of a buried 2D thick, vertically faulted slab from gravity data using the sample spacing – curves method or simply s-curves method. The method also provides an estimate for the horizontal location of the fault and a least-squares estimate for the density contrast of the slab relative to the host. The method involves using a 2D thick vertical fault model convolved with the same finite difference second horizontal gradient filter as applied to the gravity data. The synthetic examples (noise-free and noise affected) are presented to illustrate our method. The test on the real data (Central Valley of Chile) and the obtained results were consistent with the available independent observations and the broader geological aspects of this region.