Difference between revisions of "Comparison of State of the Art Visual Odometry Systems"
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{{ProjectProposal | {{ProjectProposal | ||
|title=A Comparison of State of the Art Visual Odometry Systems (Monocular and Stereo) | |title=A Comparison of State of the Art Visual Odometry Systems (Monocular and Stereo) | ||
| − | |image= | + | |image=VisualOdometry.jpg |
|description=Visual odometry is the estimation of camera(s) movement from a sequence of images. In case we deal with a single camera system we have Monocular Visual Odometry; in case we have more cameras we have a Stero Visual Odometry. The goal of the thesis is to review the state of the art on in visual odometry, classify existing approaches and compare their implementations (many of the algorithms have online source code available). | |description=Visual odometry is the estimation of camera(s) movement from a sequence of images. In case we deal with a single camera system we have Monocular Visual Odometry; in case we have more cameras we have a Stero Visual Odometry. The goal of the thesis is to review the state of the art on in visual odometry, classify existing approaches and compare their implementations (many of the algorithms have online source code available). | ||
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|tutor=MatteoMatteucci | |tutor=MatteoMatteucci | ||
| − | |start= | + | |start=2015/01/01 |
|studmin=1 | |studmin=1 | ||
|studmax=2 | |studmax=2 | ||
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|restopic=none | |restopic=none | ||
|level=Bs;Ms | |level=Bs;Ms | ||
| − | |type=Thesis | + | |type=Thesis;Course |
|status=Active | |status=Active | ||
}} | }} | ||
Latest revision as of 01:34, 22 December 2014
| Title: | A Comparison of State of the Art Visual Odometry Systems (Monocular and Stereo) |  Image:VisualOdometry.jpg |
| Description: | Visual odometry is the estimation of camera(s) movement from a sequence of images. In case we deal with a single camera system we have Monocular Visual Odometry; in case we have more cameras we have a Stero Visual Odometry. The goal of the thesis is to review the state of the art on in visual odometry, classify existing approaches and compare their implementations (many of the algorithms have online source code available).
Material
Expected outcome:
Required skills or skills to be acquired:
| |
| Tutor: | MatteoMatteucci (matteo.matteucci@polimi.it) | |
| Start: | 2015/01/01 | |
| Students: | 1 - 2 | |
| CFU: | 10 - 20 | |
| Research Area: | Computer Vision and Image Analysis | |
| Research Topic: | none | |
| Level: | Bs, Ms | |
| Type: | Thesis, Course | |
| Status: | Active |
