Academic Journal
Real-Time Refinement of Kinect Depth Maps using Multi-Resolution Anisotropic Diffusion.
| Τίτλος: | Real-Time Refinement of Kinect Depth Maps using Multi-Resolution Anisotropic Diffusion. |
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| Συγγραφείς: | Vijayanagar, Krishna, Loghman, Maziar, Kim, Joohee |
| Πηγή: | Mobile Networks & Applications; Jun2014, Vol. 19 Issue 3, p414-425, 12p |
| Θεματικοί όροι: | Kinect (Motion sensor), Gesture controlled interfaces (Computer systems), Motion detectors, Programmable controllers, Depth maps (Digital image processing) |
| Περίληψη: | In this paper, we present a novel real-time algorithm to refine depth maps generated by low-cost commercial depth sensors like the Microsoft Kinect. The Kinect sensor falls under the category of RGB-D sensors that can generate a high resolution depth map and color image of a scene. They are relatively inexpensive and are commercially available off-the-shelf. However, owing to their low complexity, there are several artifacts that one encounters in the depth map like holes, mis-alignment between the depth map and color image and lack of sharp object boundaries in the depth map. This is a potential problem in applications that require the color image to be projected in 3-D using the depth map. Such applications depend heavily on the depth map and thus the quality of the depth map is of vital importance. In this paper, a novel multi-resolution anisotropic diffusion based algorithm is presented that accepts a Kinect generated depth map and color image and computes a dense depth map in which the holes have been filled and the edges of the objects are sharpened and aligned with the objects in the color image. The proposed algorithm also ensures that regions in the depth map where the depth is properly estimated are not filtered and ensures that the depth values in the final depth map are the same values that existed in the original depth map. Experimental results are provided to demonstrate the improvement in the quality of the depth map and also execution time results are provided to prove that the proposed method can be executed in real-time. [ABSTRACT FROM AUTHOR] |
| Copyright of Mobile Networks & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Links: – Type: other Text: Availability: 0 CustomLinks: – Url: https://dx.doi.org/doi:10.1007/s11036-013-0458-7 Name: EDS - Springer Nature Journals (s7799221) Category: fullText Text: View record at Springer |
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| Header | DbId: edb DbLabel: Complementary Index An: 96773790 RelevancyScore: 835 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 834.906860351563 |
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| Items | – Name: Title Label: Title Group: Ti Data: Real-Time Refinement of Kinect Depth Maps using Multi-Resolution Anisotropic Diffusion. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Vijayanagar%2C+Krishna%22">Vijayanagar, Krishna</searchLink><br /><searchLink fieldCode="AR" term="%22Loghman%2C+Maziar%22">Loghman, Maziar</searchLink><br /><searchLink fieldCode="AR" term="%22Kim%2C+Joohee%22">Kim, Joohee</searchLink> – Name: TitleSource Label: Source Group: Src Data: Mobile Networks & Applications; Jun2014, Vol. 19 Issue 3, p414-425, 12p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Kinect+%28Motion+sensor%29%22">Kinect (Motion sensor)</searchLink><br /><searchLink fieldCode="DE" term="%22Gesture+controlled+interfaces+%28Computer+systems%29%22">Gesture controlled interfaces (Computer systems)</searchLink><br /><searchLink fieldCode="DE" term="%22Motion+detectors%22">Motion detectors</searchLink><br /><searchLink fieldCode="DE" term="%22Programmable+controllers%22">Programmable controllers</searchLink><br /><searchLink fieldCode="DE" term="%22Depth+maps+%28Digital+image+processing%29%22">Depth maps (Digital image processing)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In this paper, we present a novel real-time algorithm to refine depth maps generated by low-cost commercial depth sensors like the Microsoft Kinect. The Kinect sensor falls under the category of RGB-D sensors that can generate a high resolution depth map and color image of a scene. They are relatively inexpensive and are commercially available off-the-shelf. However, owing to their low complexity, there are several artifacts that one encounters in the depth map like holes, mis-alignment between the depth map and color image and lack of sharp object boundaries in the depth map. This is a potential problem in applications that require the color image to be projected in 3-D using the depth map. Such applications depend heavily on the depth map and thus the quality of the depth map is of vital importance. In this paper, a novel multi-resolution anisotropic diffusion based algorithm is presented that accepts a Kinect generated depth map and color image and computes a dense depth map in which the holes have been filled and the edges of the objects are sharpened and aligned with the objects in the color image. The proposed algorithm also ensures that regions in the depth map where the depth is properly estimated are not filtered and ensures that the depth values in the final depth map are the same values that existed in the original depth map. Experimental results are provided to demonstrate the improvement in the quality of the depth map and also execution time results are provided to prove that the proposed method can be executed in real-time. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Mobile Networks & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11036-013-0458-7 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 414 Subjects: – SubjectFull: Kinect (Motion sensor) Type: general – SubjectFull: Gesture controlled interfaces (Computer systems) Type: general – SubjectFull: Motion detectors Type: general – SubjectFull: Programmable controllers Type: general – SubjectFull: Depth maps (Digital image processing) Type: general Titles: – TitleFull: Real-Time Refinement of Kinect Depth Maps using Multi-Resolution Anisotropic Diffusion. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Vijayanagar, Krishna – PersonEntity: Name: NameFull: Loghman, Maziar – PersonEntity: Name: NameFull: Kim, Joohee IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2014 Type: published Y: 2014 Identifiers: – Type: issn-print Value: 1383469X Numbering: – Type: volume Value: 19 – Type: issue Value: 3 Titles: – TitleFull: Mobile Networks & Applications Type: main |
| ResultId | 1 |