dc.creator | Parra Barrero, Eloy | es |
dc.creator | Fernández Berni, Jorge | es |
dc.creator | Oliveira, Fernanda D.V.R. | es |
dc.creator | Carmona Galán, Ricardo | es |
dc.creator | Rodríguez Vázquez, Ángel Benito | es |
dc.date.accessioned | 2019-09-19T14:15:47Z | |
dc.date.available | 2019-09-19T14:15:47Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Parra Barrero, E., Fernández Berni, J., Oliveira, F.D.V.R., Carmona Galán, R. y Rodríguez Vázquez, Á.B. (2016). High-Level Performance Evaluation of Object Detection Based on Massively Parallel Focal-Plane Acceleration Requiring Minimum Pixel Area Overhead. En Proceedings of 11th International Conference on Computer Vision Theory and Applications (VISAPP) (79-85), Roma, Italia: Springer. | |
dc.identifier.uri | https://hdl.handle.net/11441/89209 | |
dc.description.abstract | Smart CMOS image sensors can leverage the inherent data-level parallelism and regular computational flow of early vision by incorporating elementary processors at pixel level. However, it comes at the cost of extra area having a strong impact on the sensor sensitivity, resolution and image quality. In this scenario, the fundamental challenge is to devise new strategies capable of boosting the performance of the targeted vision pipeline while minimally affecting the sensing function itself. Such strategies must also feature enough flexibility to accommodate particular application requirements. From these high-level specifications, we propose a focal-plane processing architecture tailored to speed up object detection via the Viola-Jones algorithm. This architecture is supported by only two extra transistors per pixel and simple peripheral digital circuitry that jointly make up a massively parallel reconfigurable processing lattice. A performance evaluation of the proposed scheme in terms of accuracy and acceleration for face detection is reported. | es |
dc.description.sponsorship | Ministerio de Economía y Competitividad TEC2012-38921-C02 | es |
dc.description.sponsorship | Junta de Andalucía TIC 2338-2013 | es |
dc.description.sponsorship | Office of Naval Research (USA) N000141410355 | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Springer | es |
dc.relation.ispartof | Proceedings of 11th International Conference on Computer Vision Theory and Applications (VISAPP) (2016), p 79-85 | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Embedded Systems | es |
dc.subject | Vision Pipeline | es |
dc.subject | Early Vision | es |
dc.subject | Smart Image Sensors | es |
dc.subject | Vision Chips | es |
dc.subject | Focal-Plane Processing | es |
dc.subject | Object Detection | es |
dc.subject | Viola-Jones Algorithm | es |
dc.subject | Performance | es |
dc.subject | Processing Acceleration | es |
dc.title | High-Level Performance Evaluation of Object Detection Based on Massively Parallel Focal-Plane Acceleration Requiring Minimum Pixel Area Overhead | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/acceptedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Electrónica y Electromagnetismo | es |
dc.relation.projectID | TEC2012-38921-C02 | es |
dc.relation.projectID | TIC 2338-2013 | es |
dc.relation.projectID | N000141410355 | es |
idus.format.extent | 7 p. | es |
dc.publication.initialPage | 79 | es |
dc.publication.endPage | 85 | es |
dc.eventtitle | Proceedings of 11th International Conference on Computer Vision Theory and Applications (VISAPP) | es |
dc.eventinstitution | Roma, Italia | es |