NDLI: High Quality Shape from a Single RGB-D Image under Uncalibrated Natural Illumination

Content Provider	IEEE Xplore Digital Library
Author	Yudeog Han Joon-Young Lee In So Kweon
Copyright Year	2013
Description	Author affiliation: Robot. & Comput. Vision Lab., KAIST, Daejeon, South Korea (Yudeog Han; Joon-Young Lee; In So Kweon)
Abstract	We present a novel framework to estimate detailed shape of diffuse objects with uniform albedo from a single RGB-D image. To estimate accurate lighting in natural illumination environment, we introduce a general lighting model consisting of two components: global and local models. The global lighting model is estimated from the RGB-D input using the low-dimensional characteristic of a diffuse reflectance model. The local lighting model represents spatially varying illumination and it is estimated by using the smoothly-varying characteristic of illumination. With both the global and local lighting model, we can estimate complex lighting variations in uncontrolled natural illumination conditions accurately. For high quality shape capture, a shape-from-shading approach is applied with the estimated lighting model. Since the entire process is done with a single RGB-D input, our method is capable of capturing the high quality shape details of a dynamic object under natural illumination. Experimental results demonstrate the feasibility and effectiveness of our method that dramatically improves shape details of the rough depth input.
Sponsorship	IEEE Comput. Soc.
Starting Page	1617
Ending Page	1624
File Size	3231525
Page Count	8
File Format	PDF
ISBN	9781479928408
ISSN	15505499
DOI	10.1109/ICCV.2013.204
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-01
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Lighting Shape Estimation Geometry Calibration Image color analysis Three-dimensional displays kinect shape-from-shading shape estimation
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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