Kinect depth map inpainting using spline approximation

Denis Brazey, C. Gout
{"title":"Kinect depth map inpainting using spline approximation","authors":"Denis Brazey, C. Gout","doi":"10.1109/EUVIP.2014.7018372","DOIUrl":null,"url":null,"abstract":"Image inpainting consists in reconstructing missing parts of a given image. In this work, we propose to use an approximation method based on splines and finite elements approximation to recover missing depth values in images acquired with a Kinect 3D sensor. Neighboring pixels in the depth map may contain very different distance values. The considered surface approximation problem therefore involves rapidly varying data which can lead to oscillations (Gibbs phenomenon). To address this issue, we propose to apply two scale transformations to dampen these oscillations near steep gradients implied by the data. The algorithm is presented with some numerical examples of inpainting. Our approach also permits to get a finer resolution of the 3D depth map.","PeriodicalId":442246,"journal":{"name":"2014 5th European Workshop on Visual Information Processing (EUVIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 5th European Workshop on Visual Information Processing (EUVIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EUVIP.2014.7018372","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Image inpainting consists in reconstructing missing parts of a given image. In this work, we propose to use an approximation method based on splines and finite elements approximation to recover missing depth values in images acquired with a Kinect 3D sensor. Neighboring pixels in the depth map may contain very different distance values. The considered surface approximation problem therefore involves rapidly varying data which can lead to oscillations (Gibbs phenomenon). To address this issue, we propose to apply two scale transformations to dampen these oscillations near steep gradients implied by the data. The algorithm is presented with some numerical examples of inpainting. Our approach also permits to get a finer resolution of the 3D depth map.
使用样条近似绘制Kinect深度图
图像修复包括重建给定图像的缺失部分。在这项工作中,我们建议使用基于样条和有限元近似的近似方法来恢复Kinect 3D传感器获取的图像中缺失的深度值。深度图中的相邻像素可能包含非常不同的距离值。因此,所考虑的表面近似问题涉及可能导致振荡的快速变化的数据(吉布斯现象)。为了解决这个问题,我们建议应用两个尺度变换来抑制数据所暗示的陡峭梯度附近的这些振荡。给出了该算法的一些数值算例。我们的方法还允许获得更精细的3D深度图分辨率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信