Dissertation/ Thesis
Obstacle detection using Microsoft Kinect
| Τίτλος: | Obstacle detection using Microsoft Kinect |
|---|---|
| Συγγραφείς: | Niclas Zeller |
| Έτος έκδοσης: | 2013 |
| Θεματικοί όροι: | Cloud computing systems, Kinect (Programmable controller) -- Programming, Multimodal user interfaces (Computer systems), Three-dimensional imaging, User interfaces (Computer systems) |
| Περιγραφή: | This thesis presents the development of image processing algorithms based on a Microsoft Kinect camera system. The algorithms developed during this thesis are applied on the depth image received from Kinect and are supposed to model a three dimensional object based representation of the recorded scene. The motivation behind this thesis is to develop a system which assists visually impaired people by navigating through unknown environments. The developed system is able to detect obstacles in the recorded scene and to warn about these obstacles. Since the goal of this thesis was not to develop a complete real time system but to invent reliable algorithms solving this task, the algorithms were developed in MATLAB. Additionally a control software was developed by which depth as well as color images can be received from Kinect. The developed algorithms are a combination of already known plane fitting algorithms and novel approaches. The algorithms perform a plane segmentation of the 3D point cloud and model objects out of the received segments. Each obstacle is defined by a cuboid box and thus can be illustrated easily to the blind person. For plane segmentation different approaches were compared to each other to find the most suitable approach. The first algorithm analyzed in this thesis is a normal vector based plane fitting algorithm. This algorithm supplies very accurate results but also has a high computation effort. The second approach, which was finally implemented, is a gradient based 2D image segmentation combined with a RANSAC plane segmentation (6) in a 3D points cloud. This approach has the advantage to find very small edges within the scene but also builds planes based on global constrains. Beside the development of the algorithm results of the image processing, which are really promising, are presented. Thus the algorithm is worth to be improved by further development. The developed algorithm is able to detect very small but significant obstacles but on the other hand does not represent the scene too ... |
| Τύπος εγγράφου: | thesis |
| Γλώσσα: | unknown |
| Relation: | https://figshare.com/articles/thesis/Obstacle_detection_using_Microsoft_Kinect/14646711 |
| DOI: | 10.32920/ryerson.14646711.v1 |
| Διαθεσιμότητα: | https://doi.org/10.32920/ryerson.14646711.v1 https://figshare.com/articles/thesis/Obstacle_detection_using_Microsoft_Kinect/14646711 |
| Rights: | In Copyright |
| Αριθμός Καταχώρησης: | edsbas.53C030E8 |
| Βάση Δεδομένων: | BASE |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://doi.org/10.32920/ryerson.14646711.v1# Name: EDS - BASE (ns324271) Category: fullText Text: View record from BASE |
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| Header | DbId: edsbas DbLabel: BASE An: edsbas.53C030E8 RelevancyScore: 697 AccessLevel: 3 PubType: Dissertation/ Thesis PubTypeId: dissertation PreciseRelevancyScore: 697.314208984375 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Obstacle detection using Microsoft Kinect – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Niclas+Zeller%22">Niclas Zeller</searchLink> – Name: DatePubCY Label: Publication Year Group: Date Data: 2013 – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Cloud+computing+systems%22">Cloud computing systems</searchLink><br /><searchLink fieldCode="DE" term="%22Kinect+%28Programmable+controller%29+--+Programming%22">Kinect (Programmable controller) -- Programming</searchLink><br /><searchLink fieldCode="DE" term="%22Multimodal+user+interfaces+%28Computer+systems%29%22">Multimodal user interfaces (Computer systems)</searchLink><br /><searchLink fieldCode="DE" term="%22Three-dimensional+imaging%22">Three-dimensional imaging</searchLink><br /><searchLink fieldCode="DE" term="%22User+interfaces+%28Computer+systems%29%22">User interfaces (Computer systems)</searchLink> – Name: Abstract Label: Description Group: Ab Data: This thesis presents the development of image processing algorithms based on a Microsoft Kinect camera system. The algorithms developed during this thesis are applied on the depth image received from Kinect and are supposed to model a three dimensional object based representation of the recorded scene. The motivation behind this thesis is to develop a system which assists visually impaired people by navigating through unknown environments. The developed system is able to detect obstacles in the recorded scene and to warn about these obstacles. Since the goal of this thesis was not to develop a complete real time system but to invent reliable algorithms solving this task, the algorithms were developed in MATLAB. Additionally a control software was developed by which depth as well as color images can be received from Kinect. The developed algorithms are a combination of already known plane fitting algorithms and novel approaches. The algorithms perform a plane segmentation of the 3D point cloud and model objects out of the received segments. Each obstacle is defined by a cuboid box and thus can be illustrated easily to the blind person. For plane segmentation different approaches were compared to each other to find the most suitable approach. The first algorithm analyzed in this thesis is a normal vector based plane fitting algorithm. This algorithm supplies very accurate results but also has a high computation effort. The second approach, which was finally implemented, is a gradient based 2D image segmentation combined with a RANSAC plane segmentation (6) in a 3D points cloud. This approach has the advantage to find very small edges within the scene but also builds planes based on global constrains. Beside the development of the algorithm results of the image processing, which are really promising, are presented. Thus the algorithm is worth to be improved by further development. The developed algorithm is able to detect very small but significant obstacles but on the other hand does not represent the scene too ... – Name: TypeDocument Label: Document Type Group: TypDoc Data: thesis – Name: Language Label: Language Group: Lang Data: unknown – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: https://figshare.com/articles/thesis/Obstacle_detection_using_Microsoft_Kinect/14646711 – Name: DOI Label: DOI Group: ID Data: 10.32920/ryerson.14646711.v1 – Name: URL Label: Availability Group: URL Data: https://doi.org/10.32920/ryerson.14646711.v1<br />https://figshare.com/articles/thesis/Obstacle_detection_using_Microsoft_Kinect/14646711 – Name: Copyright Label: Rights Group: Cpyrght Data: In Copyright – Name: AN Label: Accession Number Group: ID Data: edsbas.53C030E8 |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.53C030E8 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.32920/ryerson.14646711.v1 Languages: – Text: unknown Subjects: – SubjectFull: Cloud computing systems Type: general – SubjectFull: Kinect (Programmable controller) -- Programming Type: general – SubjectFull: Multimodal user interfaces (Computer systems) Type: general – SubjectFull: Three-dimensional imaging Type: general – SubjectFull: User interfaces (Computer systems) Type: general Titles: – TitleFull: Obstacle detection using Microsoft Kinect Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Niclas Zeller IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2013 Identifiers: – Type: issn-locals Value: edsbas |
| ResultId | 1 |