Data‐driven recovery of hand depth using CRRF on stereo images

Data‐driven recovery of hand depth using CRRF on stereo images

Hand pose is emerging as an important interface for human–computer interaction. This study presents a data‐driven method to estimate a high‐quality depth map of a hand from a stereoscopic camera input by introducing a novel superpixel‐based regression framework that takes advantage of the smoothness...

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Bibliographic Details
Main Authors: Rilwan Remilekun Basaru, Chris Child, Eduardo Alonso, Gregory Slabaugh
Format: Article
Language:English
Published: Wiley 2018-08-01
Series:IET Computer Vision
Subjects:
hand depth
CRRF
stereo images
hand pose
important interface
human–computer interaction
Online Access:https://doi.org/10.1049/iet-cvi.2017.0227

Internet

https://doi.org/10.1049/iet-cvi.2017.0227

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