3D depth information extraction with omni-directional camera
This paper presents a novel 3D depth information extraction method without calibration. Firstly, this paper develops an omni-directional 3D camera system, which consists of a CCD camera, hyperbolic mirror, infrared laser diodes and diffractive of element (DOE). Secondly, a depth measurement model is...
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| Veröffentlicht in: | Information processing letters 2015-02, Vol.115 (2), p.285-291 |
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| creator | Jia, Tong Shi, Yan Zhou, ZhongXuan Chen, DongYue |
| description | This paper presents a novel 3D depth information extraction method without calibration. Firstly, this paper develops an omni-directional 3D camera system, which consists of a CCD camera, hyperbolic mirror, infrared laser diodes and diffractive of element (DOE). Secondly, a depth measurement model is proposed to obtain the 3D depth information. Finally, in order to calculate the speckle shift accurately between the reference image and the object image, a dot matrix pattern and sequence coding algorithm are designed to find the corresponding speckles in the two images. Experimental results show that the reconstructed depth data have a good correlation with the actual distance. The accuracy of the data is also found to be influenced by the distance between the object and the camera.
•A novel omni-directional 3D camera framework is proposed.•The omni-directional camera and infrared dot matrix structured light can be merged.•The model can reveal the relation between the object depth and its pixel offset.•We can obtain the pixel offset with the sequence coding algorithm. |
| doi_str_mv | 10.1016/j.ipl.2014.09.029 |
| format | Article |
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•A novel omni-directional 3D camera framework is proposed.•The omni-directional camera and infrared dot matrix structured light can be merged.•The model can reveal the relation between the object depth and its pixel offset.•We can obtain the pixel offset with the sequence coding algorithm.</description><subject>Algorithms</subject><subject>Calibration</subject><subject>Cameras</subject><subject>CCD cameras</subject><subject>Depth measurement</subject><subject>Diffraction</subject><subject>Digital cameras</subject><subject>Diodes</subject><subject>Information retrieval</subject><subject>Infrared laser</subject><subject>Mathematical models</subject><subject>Omni-directional image</subject><subject>Real-time systems</subject><subject>Structured light</subject><subject>Studies</subject><subject>Three dimensional</subject><subject>Three dimensional imaging</subject><issn>0020-0190</issn><issn>1872-6119</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNp9kD1PxDAMhiMEEkfhB7BVYmFpsds01wgWxLd0EsvtUS5xRap-kfT4-Pf0rkwMeLFlv69lP4ydI6QIKK7q1A1NmgHyFGQKmTxgCyyXWSIQ5SFbAGSQAEo4Zich1AAgeL5csJv8PrY0jG-x66ret3p0fRfT1-i12Zefbpr1becS6zzte7qJjW7J61N2VOkm0Nlvjtj68WF995ysXp9e7m5XicmLckyw4iRKYUSudSFtIbSApTGEBmEjjSZrqyqzaPimIquRc5kVvNqg1jbnOo_Y5bx28P37lsKoWhcMNY3uqN8GhaLAXJb5FBG7-COt-62fLt6pslIUHCZtxHBWGd-H4KlSg3et9t8KQe1wqlpNONUOpwKpJpyT53r20PTohyOvgnHUGZqxKNu7f9w_kfJ9mg</recordid><startdate>20150201</startdate><enddate>20150201</enddate><creator>Jia, Tong</creator><creator>Shi, Yan</creator><creator>Zhou, ZhongXuan</creator><creator>Chen, DongYue</creator><general>Elsevier B.V</general><general>Elsevier Sequoia S.A</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0003-1424-798X</orcidid></search><sort><creationdate>20150201</creationdate><title>3D depth information extraction with omni-directional camera</title><author>Jia, Tong ; Shi, Yan ; Zhou, ZhongXuan ; Chen, DongYue</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c358t-1f4e686c63aa59d56a607cce1c10b9caeddff2d1c4bfeda1449254fb1aad34a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Algorithms</topic><topic>Calibration</topic><topic>Cameras</topic><topic>CCD cameras</topic><topic>Depth measurement</topic><topic>Diffraction</topic><topic>Digital cameras</topic><topic>Diodes</topic><topic>Information retrieval</topic><topic>Infrared laser</topic><topic>Mathematical models</topic><topic>Omni-directional image</topic><topic>Real-time systems</topic><topic>Structured light</topic><topic>Studies</topic><topic>Three dimensional</topic><topic>Three dimensional imaging</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jia, Tong</creatorcontrib><creatorcontrib>Shi, Yan</creatorcontrib><creatorcontrib>Zhou, ZhongXuan</creatorcontrib><creatorcontrib>Chen, DongYue</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Information processing letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jia, Tong</au><au>Shi, Yan</au><au>Zhou, ZhongXuan</au><au>Chen, DongYue</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>3D depth information extraction with omni-directional camera</atitle><jtitle>Information processing letters</jtitle><date>2015-02-01</date><risdate>2015</risdate><volume>115</volume><issue>2</issue><spage>285</spage><epage>291</epage><pages>285-291</pages><issn>0020-0190</issn><eissn>1872-6119</eissn><coden>IFPLAT</coden><abstract>This paper presents a novel 3D depth information extraction method without calibration. Firstly, this paper develops an omni-directional 3D camera system, which consists of a CCD camera, hyperbolic mirror, infrared laser diodes and diffractive of element (DOE). Secondly, a depth measurement model is proposed to obtain the 3D depth information. Finally, in order to calculate the speckle shift accurately between the reference image and the object image, a dot matrix pattern and sequence coding algorithm are designed to find the corresponding speckles in the two images. Experimental results show that the reconstructed depth data have a good correlation with the actual distance. The accuracy of the data is also found to be influenced by the distance between the object and the camera.
•A novel omni-directional 3D camera framework is proposed.•The omni-directional camera and infrared dot matrix structured light can be merged.•The model can reveal the relation between the object depth and its pixel offset.•We can obtain the pixel offset with the sequence coding algorithm.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.ipl.2014.09.029</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0003-1424-798X</orcidid></addata></record> |
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| ispartof | Information processing letters, 2015-02, Vol.115 (2), p.285-291 |
| issn | 0020-0190 1872-6119 |
| language | eng |
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| source | Elsevier ScienceDirect Journals |
| subjects | Algorithms Calibration Cameras CCD cameras Depth measurement Diffraction Digital cameras Diodes Information retrieval Infrared laser Mathematical models Omni-directional image Real-time systems Structured light Studies Three dimensional Three dimensional imaging |
| title | 3D depth information extraction with omni-directional camera |
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