Fast Detection of Jitter Artifacts in Human Motion Capture Models

Mateusz Pawłowicz, Witold Alda, Krzysztof Boryczko

2025

Abstract

Motion capture is the standard when it comes to acquiring detailed motion data for animations. The method is used for high-quality productions in many industries, such as filmmaking and game development. The quality of the outcome and the time needed to achieve it are incomparable with the keyframe-based manual method. However, the motion capture data sometimes gets corrupted, which results in animation artifacts that make it unrealistic and unpleasant to watch. An example of such an artifact is a jitter, which can be defined as the rapid and chaotic movement of a joint. In this work, we focus on detecting the jitter in animation sequences created using motion capture systems. To achieve that, here is proposed a multilevel analysis framework that consists of two metrics: Movement Dynamics Clutter (MDC) and Movement Dynamics Clutter Spectrum Strength (MDCSS). The former measures the dynamics of a joint, while the latter metric allows the classification of a sequence of frames as a jitter. The framework was evaluated on popular datasets to analyze the properties of the metrics. The results of our experiments revealed that two of the popular animation datasets, LAFAN1 and Human3.6M, contain instances of jitter, which was not known before inspection with our method.

Paper Citation

in Harvard Style

Pawłowicz M., Alda W. and Boryczko K. (2025). Fast Detection of Jitter Artifacts in Human Motion Capture Models. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP; ISBN 978-989-758-728-3, SciTePress, pages 77-88. DOI: 10.5220/0013144400003912

in Bibtex Style

@conference{grapp25,
author={Mateusz Pawłowicz and Witold Alda and Krzysztof Boryczko},
title={Fast Detection of Jitter Artifacts in Human Motion Capture Models},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP},
year={2025},
pages={77-88},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013144400003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP
TI - Fast Detection of Jitter Artifacts in Human Motion Capture Models
SN - 978-989-758-728-3
AU - Pawłowicz M.
AU - Alda W.
AU - Boryczko K.
PY - 2025
SP - 77
EP - 88
DO - 10.5220/0013144400003912
PB - SciTePress