TY - JOUR

T1 - Human Pose Estimation from Video and IMUs

AU - Von Marcard, Timo

AU - Pons-Moll, Gerard

AU - Rosenhahn, Bodo

PY - 2016/8/1

Y1 - 2016/8/1

N2 - In this work, we present an approach to fuse video with sparse orientation data obtained from inertial sensors to improve and stabilize full-body human motion capture. Even though video data is a strong cue for motion analysis, tracking artifacts occur frequently due to ambiguities in the images, rapid motions, occlusions or noise. As a complementary data source, inertial sensors allow for accurate estimation of limb orientations even under fast motions. However, accurate position information cannot be obtained in continuous operation. Therefore, we propose a hybrid tracker that combines video with a small number of inertial units to compensate for the drawbacks of each sensor type: on the one hand, we obtain drift-free and accurate position information from video data and, on the other hand, we obtain accurate limb orientations and good performance under fast motions from inertial sensors. In several experiments we demonstrate the increased performance and stability of our human motion tracker.

AB - In this work, we present an approach to fuse video with sparse orientation data obtained from inertial sensors to improve and stabilize full-body human motion capture. Even though video data is a strong cue for motion analysis, tracking artifacts occur frequently due to ambiguities in the images, rapid motions, occlusions or noise. As a complementary data source, inertial sensors allow for accurate estimation of limb orientations even under fast motions. However, accurate position information cannot be obtained in continuous operation. Therefore, we propose a hybrid tracker that combines video with a small number of inertial units to compensate for the drawbacks of each sensor type: on the one hand, we obtain drift-free and accurate position information from video data and, on the other hand, we obtain accurate limb orientations and good performance under fast motions from inertial sensors. In several experiments we demonstrate the increased performance and stability of our human motion tracker.

KW - animation

KW - Human pose estimation

KW - IMU

KW - inertial sensors

KW - motion capture

KW - multisensor fusion

UR - http://www.scopus.com/inward/record.url?scp=84978427623&partnerID=8YFLogxK

U2 - 10.1109/tpami.2016.2522398

DO - 10.1109/tpami.2016.2522398

M3 - Article

C2 - 26829774

AN - SCOPUS:84978427623

VL - 38

SP - 1533

EP - 1547

JO - IEEE Transactions on Pattern Analysis and Machine Intelligence

JF - IEEE Transactions on Pattern Analysis and Machine Intelligence

SN - 0162-8828

IS - 8

M1 - 7393844

ER -