Hand Segmentation for Hand-Object Interaction from Depth map

Hand segmentation for hand-object interaction is a necessary preprocessing step in many applications such as augmented reality, medical application, and human-robot interaction. However, typical methods are based on color information which is not robust to objects with skin color, skin pigment diffe...

Full description

Saved in:
Bibliographic Details
Published in:arXiv.org 2018-01
Main Authors: Kang, Byeongkeun, Kar-Han, Tan, Jiang, Nan, Hung-Shuo Tai, Tretter, Daniel, Nguyen, Truong Q
Format: Article
Language:English
Subjects:
Augmented reality
Color
Decision trees
Human engineering
Robots
Segmentation
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Hand segmentation for hand-object interaction is a necessary preprocessing step in many applications such as augmented reality, medical application, and human-robot interaction. However, typical methods are based on color information which is not robust to objects with skin color, skin pigment difference, and light condition variations. Thus, we propose hand segmentation method for hand-object interaction using only a depth map. It is challenging because of the small depth difference between a hand and objects during an interaction. To overcome this challenge, we propose the two-stage random decision forest (RDF) method consisting of detecting hands and segmenting hands. To validate the proposed method, we demonstrate results on the publicly available dataset of hand segmentation for hand-object interaction. The proposed method achieves high accuracy in short processing time comparing to the other state-of-the-art methods.
ISSN:2331-8422