RT Journal Article
T1 Parallelization strategies for markerless human motion capture
A1 Cano, Alberto
A1 Yeguas-Bolivar, Enrique
A1 Munoz-Salinas, Rafael
A1 Medina-Carnicer, Rafael
A1 Ventura, Sebastian
K1 Markerless motion capture (MMOCAP)
K1 GPU
K1 Tracking
K1 3d human motion
K1 Body motion
K1 Tracking
K1 Stereophotogrammetry
K1 Evolution
AB Markerless motion capture (MMOCAP) is the problem of determining the pose of a person from images captured by one or several cameras simultaneously without using markers on the subject. Evaluation of the solutions is frequently the most time-consuming task, making most of the proposed methods inapplicable in real-time scenarios. This paper presents an efficient approach to parallelize the evaluation of the solutions in CPUs and GPUs. Our proposal is experimentally compared on six sequences of the HumanEva-I dataset using the CMAES algorithm. Multiple algorithm's configurations were tested to analyze the best trade-off with regard to the accuracy and computing time. The proposed methods obtain speedups of 8 in multi-core CPUs, 30 in a single GPU and up to 110 using 4 GPUs.
PB Springer heidelberg
SN 1861-8200
YR 2018
FD 2018-02-01
LK https://hdl.handle.net/10668/28194
UL https://hdl.handle.net/10668/28194
LA en
DS RISalud
RD Apr 7, 2025