Selecting the motion ground truth for loose-fitting wearables: benchmarking optical MoCap methods

TL;DR

This paper introduces DrapeMoCapBench, a benchmark for evaluating optical marker-based and marker-less motion capture methods on loose garments, revealing that marker-less approaches can outperform marker-based systems in casual activities.

Contribution

The paper presents a comprehensive benchmark dataset and evaluation framework for comparing optical marker-based and marker-less MoCap methods on loose-fitting garments.

Findings

Marker-less MoCap slightly outperforms marker-based in casual activities.

Both methods experience over 10cm accuracy loss on loose garments.

Marker-less MoCap offers a cost-effective alternative for wearable motion capture.

Abstract

To help smart wearable researchers choose the optimal ground truth methods for motion capturing (MoCap) for all types of loose garments, we present a benchmark, DrapeMoCapBench (DMCB), specifically designed to evaluate the performance of optical marker-based and marker-less MoCap. High-cost marker-based MoCap systems are well-known as precise golden standards. However, a less well-known caveat is that they require skin-tight fitting markers on bony areas to ensure the specified precision, making them questionable for loose garments. On the other hand, marker-less MoCap methods powered by computer vision models have matured over the years, which have meager costs as smartphone cameras would suffice. To this end, DMCB uses large real-world recorded MoCap datasets to perform parallel 3D physics simulations with a wide range of diversities: six levels of drape from skin-tight to extremely draped garments, three levels of motions and six body type - gender combinations to benchmark state-of-the-art optical marker-based and marker-less MoCap methods to identify the best-performing method in different scenarios. In assessing the performance of marker-based and low-cost marker-less MoCap for casual loose garments both approaches exhibit significant performance loss (>10cm), but for everyday activities involving basic and fast motions, marker-less MoCap slightly outperforms marker-based MoCap, making it a favorable and cost-effective choice for wearable studies.