https://scholars.lib.ntu.edu.tw/handle/123456789/155225
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | SOO-CHANG PEI | en |
dc.contributor.author | Liou, Lin-Gwo | en |
dc.creator | Pei, Soo-Chang; Liou, Lin-Gwo | - |
dc.date | 1998 | en |
dc.date.accessioned | 2009-03-04T06:36:48Z | - |
dc.date.accessioned | 2018-07-06T15:44:11Z | - |
dc.date.available | 2009-03-04T06:36:48Z | - |
dc.date.available | 2018-07-06T15:44:11Z | - |
dc.date.issued | 1998 | - |
dc.identifier.issn | 00313203 | - |
dc.identifier.uri | http://ntur.lib.ntu.edu.tw//handle/246246/142448 | - |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-0032021248&doi=10.1016%2fs0031-3203%2897%2900044-7&partnerID=40&md5=55715656786f9a36831cecd84a09d3a5 | - |
dc.description.abstract | Three-dimensional (3D) motion estimation is a very important topic in machine vision. However, reliability of the estimated 3D motion seems to be the most challenging problem, especially to the linear algorithms developed for solving a general 3D motion problem (six degrees of freedom). In real applications such as the traffic surveillance and auto-vehicle systems, the observed 3D motion has only three degrees of freedom because of the ground plane constraint (GPC). In this paper, a new iterative method is proposed for solving the above problem. Our method has several advantages: (1) It can handle both the point and line features as its input image data. (2) It is very suitable for parallel processing. (3) Its cost function is so well-conditioned that the final 3D motion estimation is robust and insensitive to noise, which is proved by experiments. (4) It can handle the case of missing data to a certain degree. The above benefits make our method suitable for a real application. Experiments including simulated and real-world images show satisfactory results. © 1997 Pattern Recognition Society. Published by Elsevier Science Ltd. | - |
dc.format | application/pdf | en |
dc.format.extent | 956187 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language | en | en |
dc.language.iso | en_US | - |
dc.relation.ispartof | Pattern Recognition | en_US |
dc.subject | Ground plane constraint; Image lines; Image points; Traffic surveillance system | - |
dc.subject.other | Algorithms; Computer vision; Constraint theory; Degrees of freedom (mechanics); Image analysis; Iterative methods; Parallel processing systems; Problem solving; Three dimensional; Ground plane constraint; Image point; Line features; Motion estimation; Traffic surveillance system; Feature extraction | - |
dc.title | Vehicle-type motion estimation by the fusion of image point and line features | en |
dc.type | journal article | en |
dc.identifier.doi | 10.1016/s0031-3203(97)00044-7 | - |
dc.identifier.scopus | 2-s2.0-0032021248 | - |
dc.relation.pages | 333-344 | - |
dc.relation.journalvolume | 31 | - |
dc.relation.journalissue | 3 | - |
dc.identifier.uri.fulltext | http://ntur.lib.ntu.edu.tw/bitstream/246246/142448/1/38.pdf | - |
item.fulltext | with fulltext | - |
item.languageiso639-1 | en_US | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.cerifentitytype | Publications | - |
item.openairetype | journal article | - |
item.grantfulltext | open | - |
crisitem.author.dept | Photonics and Optoelectronics | - |
crisitem.author.dept | Networking and Multimedia | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
顯示於: | 電機工程學系 |
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