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Enhanced computer vision with microsoft kinect sensor: A review (2013)
| Venue: | IEEE TRANSACTIONS ON CYBERNETICS |
| Citations: | 31 - 2 self |
BibTeX
@ARTICLE{Han13enhancedcomputer,
author = {Jungong Han and Ling Shao and Dong Xu and Jamie Shotton},
title = {Enhanced computer vision with microsoft kinect sensor: A review},
journal = {IEEE TRANSACTIONS ON CYBERNETICS},
year = {2013}
}
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Abstract
With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use. The complementary nature of the depth and visual information provided by the Kinect sensor opens up new opportunities to solve fundamental problems in computer vision. This paper presents a comprehensive review of recent Kinect-based computer vision algorithms and applications. The reviewed approaches are classified according to the type of vision problems that can be addressed or enhanced by means of the Kinect sensor. The covered topics include preprocessing, object tracking and recognition, human activity analysis, hand gesture analysis, and indoor 3-D mapping. For each category of methods, we outline their main algorithmic contributions and summarize their advantages/differences compared to their RGB counterparts. Finally, we give an overview of the challenges in this field and future research trends. This paper is expected to serve as a tutorial and source of references for Kinect-based computer vision researchers.
Keyphrases
kinect sensor microsoft kinect sensor enhanced computer vision reviewed approach comprehensive review depth image high-resolution depth advantage difference rgb counterpart recent kinect-based computer vision algorithm hand gesture analysis information fusion computer vision visual information indoor 3-d mapping covered topic widespread use complementary nature low-cost microsoft kinect sensor fundamental problem future research trend human activity analysis object tracking index term computer vision kinect-based computer vision researcher vision problem main algorithmic contribution new opportunity
