Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/88230
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Flint, A. | - |
dc.contributor.author | Murray, D. | - |
dc.contributor.author | Reid, I. | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | Proceedings / IEEE International Conference on Computer Vision. IEEE International Conference on Computer Vision, 2011, pp.2228-2235 | - |
dc.identifier.isbn | 9781457711015 | - |
dc.identifier.issn | 1550-5499 | - |
dc.identifier.uri | http://hdl.handle.net/2440/88230 | - |
dc.description.abstract | This paper addresses scene understanding in the context of a moving camera, integrating semantic reasoning ideas from monocular vision with 3D information available through structure-from-motion. We combine geometric and photometric cues in a Bayesian framework, building on recent successes leveraging the indoor Manhattan assumption in monocular vision. We focus on indoor environments and show how to extract key boundaries while ignoring clutter and decorations. To achieve this we present a graphical model that relates photometric cues learned from labeled data, stereo photo-consistency across multiple views, and depth cues derived from structure-from-motion point clouds. We show how to solve MAP inference using dynamic programming, allowing exact, global inference in ~100 ms (in addition to feature computation of under one second) without using specialized hardware. Experiments show our system out-performing the state-of-the-art. | - |
dc.description.statementofresponsibility | Alex Flint, David Murray, and Ian Reid | - |
dc.language.iso | en | - |
dc.publisher | IEEE | - |
dc.relation.ispartofseries | IEEE International Conference on Computer Vision | - |
dc.rights | ©2011 IEEE | - |
dc.source.uri | http://dx.doi.org/10.1109/iccv.2011.6126501 | - |
dc.title | Manhattan scene understanding using monocular, stereo, and 3D features | - |
dc.type | Conference paper | - |
dc.contributor.conference | 2011 IEEE International Conference on Computer Vision (ICCV) (6 Nov 2011 - 13 Nov 2011 : Barcelona, Spain) | - |
dc.identifier.doi | 10.1109/ICCV.2011.6126501 | - |
dc.publisher.place | USA | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Reid, I. [0000-0001-7790-6423] | - |
Appears in Collections: | Aurora harvest 2 Computer Science publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
RA_hdl_88230.pdf Restricted Access | Restricted Access | 1.5 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.