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Robust multi-dimensional motion features for first-person vision activity recognition
dc.contributor.author | Abebe, Girmaw |
dc.contributor.author | Cavallaro, Andrea |
dc.contributor.author | Llanas Parra, Francesc Xavier |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.date.accessioned | 2016-07-18T07:03:34Z |
dc.date.available | 2016-07-18T07:03:34Z |
dc.date.issued | 2016-08 |
dc.identifier.citation | Abebe, G., Cavallaro, A., Llanas, F. Robust multi-dimensional motion features for first-person vision activity recognition. "Computer vision and image understanding", Agost 2016, vol. 149, p. 229-248. |
dc.identifier.issn | 1077-3142 |
dc.identifier.uri | http://hdl.handle.net/2117/88837 |
dc.description.abstract | We propose robust multi-dimensional motion features for human activity recognition from first-person videos. The proposed features encode information about motion magnitude, direction and variation, and combine them with virtual inertial data generated from the video itself. The use of grid flow representation, per-frame normalization and temporal feature accumulation enhances the robustness of our new representation. Results on multiple datasets demonstrate that the proposed feature representation outperforms existing motion features, and importantly it does so independently of the classifier. Moreover, the proposed multi-dimensional motion features are general enough to make them suitable for vision tasks beyond those related to wearable cameras. (C) 2015 The Authors. Published by Elsevier Inc. |
dc.format.extent | 20 p. |
dc.language.iso | eng |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació::Interacció home-màquina |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes |
dc.subject.lcsh | Human activity recognition |
dc.subject.other | Human activity recognition |
dc.subject.other | First-person vision |
dc.subject.other | Grid optical flow |
dc.subject.other | Inertial data |
dc.subject.other | Wearable camera |
dc.subject.other | Physical-activity |
dc.subject.other | Triaxial accelerometer |
dc.subject.other | Wearable sensors |
dc.subject.other | Camera |
dc.subject.other | Acceleration |
dc.subject.other | SVM |
dc.title | Robust multi-dimensional motion features for first-person vision activity recognition |
dc.type | Article |
dc.subject.lemac | Reconeixement de formes (Informàtica) |
dc.contributor.group | Universitat Politècnica de Catalunya. CETpD -Centre d'Estudis Tecnològics per a l'Atenció a la Dependència i la Vida Autònoma |
dc.identifier.doi | 10.1016/j.cviu.2015.10.015 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://www.sciencedirect.com/science/article/pii/S1077314215002350 |
dc.rights.access | Open Access |
local.identifier.drac | 18770956 |
dc.description.version | Postprint (published version) |
local.citation.author | Abebe, G.; Cavallaro, A.; Llanas, F. |
local.citation.publicationName | Computer vision and image understanding |
local.citation.volume | 149 |
local.citation.startingPage | 229 |
local.citation.endingPage | 248 |
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