RT Journal Article
T1 Mixing body-parts model for 2D human pose estimation in stereo videos
A1 Lopez-Quintero, Manuel I.
A1 Marin-Jimenez, Manuel J.
A1 Munoz-Salinas, Rafael
A1 Medina-Carnicer, Rafael
K1 Stereo image processing
K1 Pose estimation
K1 Video signal processing
K1 Image sensors
K1 Image sequences
K1 Stereo videos
K1 Mixing body-parts model
K1 2D articulated human pose estimation
K1 Microsoft Kinect
K1 Controlled indoor environments
K1 Localise upper-body keypoints
K1 Temporal sequences
K1 Stereo image pairs
K1 Body poses
K1 Stereo consistency
K1 Temporal consistency
K1 Stereo human pose estimation dataset
K1 INRIA 3DMovie
K1 Monocular sequences
K1 Stereo sequences
AB This study targets 2D articulated human pose estimation (i.e. localisation of body limbs) in stereo videos. Although in recent years depth-based devices (e.g. Microsoft Kinect) have gained popularity, as they perform very well in controlled indoor environments (e.g. living rooms, operating theatres or gyms), they suffer clear problems in outdoor scenarios and, therefore, human pose estimation is still an interesting unsolved problem. The authors propose here a novel approach that is able to localise upper-body keypoints (i.e. shoulders, elbows, and wrists) in temporal sequences of stereo image pairs. The authors' method starts by locating and segmenting people in the image pairs by using disparity and appearance information. Then, a set of candidate body poses is computed for each view independently. Finally, temporal and stereo consistency is applied to estimate a final 2D pose. The authors' validate their model on three challenging datasets: stereo human pose estimation dataset', poses in the wild' and INRIA 3DMovie'. The experimental results show that the authors' model not only establishes new state-of-the-art results on stereo sequences, but also brings improvements in monocular sequences.
PB Wiley
SN 1751-9632
YR 2017
FD 2017-03-11
LK http://hdl.handle.net/10668/18921
UL http://hdl.handle.net/10668/18921
LA en
NO López‐Quintero MI, Marín‐Jiménez MJ, Muñoz‐Salinas R, Medina‐Carnicer R. Mixing body‐parts model for 2D human pose estimation in stereo videos. IET Computer Vision [Internet]. 18 de julio de 2017;11(6):426-33
DS RISalud
RD Apr 9, 2025