Sentence examples for motion capture datasets from inspiring English sources

Experiment section describes the experimental process for the collection of motion capture datasets with both a Kinect and a VICON.

Despite the robust performance on various motion capture datasets, limitation of its application is also obvious, i.e., the object deformation should be temporally continuous and smooth.

For the assessment, experimental studies were undertaken to collect motion capture datasets using an RGB-D sensor and a marker-based motion capture system, VICON, and to analyze errors as compared with the VICON used as the ground truth.

As a test case, 25 trials of ascending and descending during ladder climbing were recorded simultaneously with both systems, and the resulting motion capture datasets (i.e., 3D skeleton models) were temporally and spatially synchronized for their comparison.

To evaluate the performance of the Kinect for motion analysis, we applied a motion detection method (Han et al. 2013) to motion capture datasets from a Kinect and a VICON, and compared the results of detection based on conventional measures of classification performances (i.e., accuracy, precision, and recall).

In this article, we present a large 3D motion capture dataset of Taijiquan martial art gestures (n = 2200 samples) that includes 13 classes (relative to Taijiquan techniques) executed by 12 participants of various skill levels.

The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt.

To show the potential performance of our proposed method when the skeleton tracking is almost perfect, we used the motion capture dataset provided by Carnegie Mellon University, which contains actions captured at 120 fps [28].

Despite this, the intensive use of a motion capture system can provide large datasets of human actions, and the datasets can be used to facilitate handling the variety of actions to be classified.

Our test is carried out on two face datasets, i.e., the Vicon motion capture data Mocap-Face [9] and the Binghamton University 3D Facial Expression (BU-3DFE) dataset [30].

"Motion capture is good at large motions," he said.