Extrapolation algorithms for raw depth maps captured by kinect sensor

Depth map contains depth information of a scene that measures the distances from a viewpoint to the objects and surfaces in the scene. It has wide applications in 3D computer graphics. Microsoft Kinect sensor provides a simple and accessible way to obtain depth maps. However, almost every raw depth...

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Main Author: Liu, Fengjiao.
Other Authors: Ma Kai Kuang
Format: Final Year Project
Language:English
Published: 2012
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Online Access:http://hdl.handle.net/10356/49311
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-493112023-07-07T17:11:20Z Extrapolation algorithms for raw depth maps captured by kinect sensor Liu, Fengjiao. Ma Kai Kuang School of Electrical and Electronic Engineering Temasek Laboratories @ NTU DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Depth map contains depth information of a scene that measures the distances from a viewpoint to the objects and surfaces in the scene. It has wide applications in 3D computer graphics. Microsoft Kinect sensor provides a simple and accessible way to obtain depth maps. However, almost every raw depth map captured by Kinect has some “hole” regions where the real depth values are missing. The objective of the project is to extrapolate (to predict and fill) the “holes” with proper depth values. In the report, four extrapolation algorithms are proposed with the first three implemented offline and the last one implemented in real time. The proposed algorithms use different kinds of available information and apply to different kinds of “holes” on raw depth maps. The mean value inpainting (MVI) algorithm uses the depth information on a global base. It can give smooth depth transitions but not sharp object boundaries. The similar color based median filter (SCBMF) algorithm uses both depth and color information on a local base. It can give sharp object boundaries but not smooth depth transitions. The segmentation based median filter (SBMF) algorithm is similar to the second algorithm except that the two algorithms use the color information in different ways. The spatial mode and temporal weighted mean (SMATWM) algorithm uses depth information on a local base and time information on a global base. It is applicable to small “hole” regions. It improves the visual effect of depth frames significantly in simple real-time implementation. In the future, an adaptive extrapolation algorithm and its fast algorithm can be developed to select the most suitable algorithm for different kinds of “holes” in a single depth map and to achieve real-time extrapolation. Bachelor of Engineering 2012-05-17T06:14:35Z 2012-05-17T06:14:35Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/49311 en Nanyang Technological University 62 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Liu, Fengjiao.
Extrapolation algorithms for raw depth maps captured by kinect sensor
description Depth map contains depth information of a scene that measures the distances from a viewpoint to the objects and surfaces in the scene. It has wide applications in 3D computer graphics. Microsoft Kinect sensor provides a simple and accessible way to obtain depth maps. However, almost every raw depth map captured by Kinect has some “hole” regions where the real depth values are missing. The objective of the project is to extrapolate (to predict and fill) the “holes” with proper depth values. In the report, four extrapolation algorithms are proposed with the first three implemented offline and the last one implemented in real time. The proposed algorithms use different kinds of available information and apply to different kinds of “holes” on raw depth maps. The mean value inpainting (MVI) algorithm uses the depth information on a global base. It can give smooth depth transitions but not sharp object boundaries. The similar color based median filter (SCBMF) algorithm uses both depth and color information on a local base. It can give sharp object boundaries but not smooth depth transitions. The segmentation based median filter (SBMF) algorithm is similar to the second algorithm except that the two algorithms use the color information in different ways. The spatial mode and temporal weighted mean (SMATWM) algorithm uses depth information on a local base and time information on a global base. It is applicable to small “hole” regions. It improves the visual effect of depth frames significantly in simple real-time implementation. In the future, an adaptive extrapolation algorithm and its fast algorithm can be developed to select the most suitable algorithm for different kinds of “holes” in a single depth map and to achieve real-time extrapolation.
author2 Ma Kai Kuang
author_facet Ma Kai Kuang
Liu, Fengjiao.
format Final Year Project
author Liu, Fengjiao.
author_sort Liu, Fengjiao.
title Extrapolation algorithms for raw depth maps captured by kinect sensor
title_short Extrapolation algorithms for raw depth maps captured by kinect sensor
title_full Extrapolation algorithms for raw depth maps captured by kinect sensor
title_fullStr Extrapolation algorithms for raw depth maps captured by kinect sensor
title_full_unstemmed Extrapolation algorithms for raw depth maps captured by kinect sensor
title_sort extrapolation algorithms for raw depth maps captured by kinect sensor
publishDate 2012
url http://hdl.handle.net/10356/49311
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