dc.contributor.author | Chang, YY | |
dc.contributor.author | Mazzon, R | |
dc.contributor.author | Cavallaro, A | |
dc.date.accessioned | 2019-01-31T11:19:47Z | |
dc.date.available | 2019-01-31T11:19:47Z | |
dc.date.issued | 2018-11-29 | |
dc.identifier.citation | Chang, Y., Mazzon, R. and Cavallaro, A. (2018). Real-Time Quality Assessment of Videos from Body-Worn Cameras. 2018 26th European Signal Processing Conference (EUSIPCO). [online] Available at: https://ieeexplore.ieee.org/document/8553612 [Accessed 31 Jan. 2019]. | en_US |
dc.identifier.isbn | 9789082797015 | |
dc.identifier.issn | 2219-5491 | |
dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/55050 | |
dc.description.abstract | Videos captured with body-worn cameras may be affected by distortions such as motion blur, overexposure and reduced contrast. Automated video quality assessment is therefore important prior to auto-tagging, event or object recognition, or automated editing. In this paper, we present M-BRISQUE, a spatial quality evaluator that combines, in real-time, the Michelson contrast with features from the Blind/Referenceless Image Spatial QUality Evaluator. To link the resulting quality score to human judgement, we train a Support Vector Regressor with Radial Basis Function kernel on the Computational and Subjective Image Quality database. We show an example of application of M-BRISQUE in automatic editing of multi-camera content using relative view quality, and validate its predictive performance with a subjective evaluation and two public datasets. | en_US |
dc.format.extent | 2160 - 2164 | |
dc.publisher | IEEE | en_US |
dc.title | Real-time quality assessment of videos from body-worn cameras | en_US |
dc.type | Conference Proceeding | en_US |
dc.rights.holder | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |
dc.identifier.doi | 10.23919/EUSIPCO.2018.8553612 | |
pubs.notes | Not known | en_US |
pubs.publication-status | Published | en_US |
pubs.volume | 2018-September | en_US |
rioxxterms.funder | Default funder | en_US |
rioxxterms.identifier.project | Default project | en_US |