Kinect depth map enhancement
Kinect is a depth sensor and it is getting popular among the researchers and amateurs due to its cheap cost and reasonable performance. Due to the limitations of the Kinect hardware, some of the depth information is missing and the resultant depth map is too noisy to be useful for many real-life app...
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sg-ntu-dr.10356-531392023-07-07T15:51:19Z Kinect depth map enhancement Tun, Kyaw Oo. Ma Kai Kuang School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Kinect is a depth sensor and it is getting popular among the researchers and amateurs due to its cheap cost and reasonable performance. Due to the limitations of the Kinect hardware, some of the depth information is missing and the resultant depth map is too noisy to be useful for many real-life applications. This paper presents two techniques to estimate the missing information. One way to estimate is by applying median filter to the neighbor pixels. Another one is to use segmentation on the RGB image and then estimate the missing information based on the RGB segmentation, based on the observation that nearby pixels with the similar color will have the same depth. The algorithms proposed are able to recover most of the missing information. The segmentation method is able to retain the original object shape while extrapolating and it takes 4.8 seconds to complete. With most of noise removed, one will be easier to identity the objects in the enhanced depth map and it will also be better suited for other applications to leverage the depth information. Bachelor of Engineering 2013-05-30T03:52:58Z 2013-05-30T03:52:58Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/53139 en Nanyang Technological University 51 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Tun, Kyaw Oo. Kinect depth map enhancement |
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Kinect is a depth sensor and it is getting popular among the researchers and amateurs due to its cheap cost and reasonable performance. Due to the limitations of the Kinect hardware, some of the depth information is missing and the resultant depth map is too noisy to be useful for many real-life applications. This paper presents two techniques to estimate the missing information. One way to estimate is by applying median filter to the neighbor pixels. Another one is to use segmentation on the RGB image and then estimate the missing information based on the RGB segmentation, based on the observation that nearby pixels with the similar color will have the same depth. The algorithms proposed are able to recover most of the missing information. The segmentation method is able to retain the original object shape while extrapolating and it takes 4.8 seconds to complete. With most of noise removed, one will be easier to identity the objects in the enhanced depth map and it will also be better suited for other applications to leverage the depth information. |
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Ma Kai Kuang |
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Ma Kai Kuang Tun, Kyaw Oo. |
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Final Year Project |
author |
Tun, Kyaw Oo. |
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Tun, Kyaw Oo. |
title |
Kinect depth map enhancement |
title_short |
Kinect depth map enhancement |
title_full |
Kinect depth map enhancement |
title_fullStr |
Kinect depth map enhancement |
title_full_unstemmed |
Kinect depth map enhancement |
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kinect depth map enhancement |
publishDate |
2013 |
url |
http://hdl.handle.net/10356/53139 |
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1772827392349306880 |