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Article: A Kalman filter approach to direct depth estimation incorporating surface structure
Title | A Kalman filter approach to direct depth estimation incorporating surface structure |
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Authors | |
Keywords | Depth-from-motion Gradient method Image sequence Kaiman filter Surface structure |
Issue Date | 1999 |
Publisher | I E E E. The Journal's web site is located at http://www.computer.org/tpami |
Citation | Ieee Transactions On Pattern Analysis And Machine Intelligence, 1999, v. 21 n. 6, p. 570-575 How to Cite? |
Abstract | The problem of depth-from-motion using a monocular image sequence is considered. A pixel-based model is developed for direct depth estimation within a Kaiman filtering framework. A method is proposed for incorporating local surface structure into the Kaiman filter. Experimental results are provided to illustrate the effect of structural information on depth estimation. ©1999 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/42792 |
ISSN | 2023 Impact Factor: 20.8 2023 SCImago Journal Rankings: 6.158 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hung, YS | en_HK |
dc.contributor.author | Ho, HT | en_HK |
dc.date.accessioned | 2007-03-23T04:32:18Z | - |
dc.date.available | 2007-03-23T04:32:18Z | - |
dc.date.issued | 1999 | en_HK |
dc.identifier.citation | Ieee Transactions On Pattern Analysis And Machine Intelligence, 1999, v. 21 n. 6, p. 570-575 | en_HK |
dc.identifier.issn | 0162-8828 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/42792 | - |
dc.description.abstract | The problem of depth-from-motion using a monocular image sequence is considered. A pixel-based model is developed for direct depth estimation within a Kaiman filtering framework. A method is proposed for incorporating local surface structure into the Kaiman filter. Experimental results are provided to illustrate the effect of structural information on depth estimation. ©1999 IEEE. | en_HK |
dc.format.extent | 428640 bytes | - |
dc.format.extent | 100664 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.format.mimetype | application/pdf | - |
dc.language | eng | en_HK |
dc.publisher | I E E E. The Journal's web site is located at http://www.computer.org/tpami | en_HK |
dc.relation.ispartof | IEEE Transactions on Pattern Analysis and Machine Intelligence | en_HK |
dc.rights | ©1999 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | - |
dc.subject | Depth-from-motion | en_HK |
dc.subject | Gradient method | en_HK |
dc.subject | Image sequence | en_HK |
dc.subject | Kaiman filter | en_HK |
dc.subject | Surface structure | en_HK |
dc.title | A Kalman filter approach to direct depth estimation incorporating surface structure | en_HK |
dc.type | Article | en_HK |
dc.identifier.openurl | http://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0162-8828&volume=21&issue=6&spage=570&epage=575&date=1999&atitle=A+Kalman+filter+approach+to+direct+depth+estimation+incorporating+surface+structure | en_HK |
dc.identifier.email | Hung, YS:yshung@eee.hku.hk | en_HK |
dc.identifier.authority | Hung, YS=rp00220 | en_HK |
dc.description.nature | published_or_final_version | en_HK |
dc.identifier.doi | 10.1109/34.771330 | en_HK |
dc.identifier.scopus | eid_2-s2.0-0032637223 | en_HK |
dc.identifier.hkuros | 44376 | - |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-0032637223&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 21 | en_HK |
dc.identifier.issue | 6 | en_HK |
dc.identifier.spage | 570 | en_HK |
dc.identifier.epage | 575 | en_HK |
dc.identifier.isi | WOS:000080819100009 | - |
dc.publisher.place | United States | en_HK |
dc.identifier.scopusauthorid | Hung, YS=8091656200 | en_HK |
dc.identifier.scopusauthorid | Ho, HT=14067455800 | en_HK |
dc.identifier.citeulike | 10564676 | - |
dc.identifier.issnl | 0162-8828 | - |