dc.creator |
Negri, Pablo |
|
dc.date.accessioned |
2018-10-12T19:05:16Z |
|
dc.date.available |
2018-10-12T19:05:16Z |
|
dc.date.issued |
2018 |
|
dc.identifier.uri |
http://hdl.handle.net/123456789/7577 |
|
dc.description |
Disponible en: https://arxiv.org/abs/1802.03327 |
es |
dc.description.abstract |
Address Event Representation is a thriving technology that can change the digital
image processing paradigm. This paper proposes a methodology to characterize
the shape of objects using the streaming of asynchronous events. A
new descriptor that enhances spikes connectivity is associated with two oriented
histogram based representations. This paper uses those features to develop
both a non-supervised and supervised multi-classification framework to
recognize poker signs from the Poker-DVS public dataset. |
es |
dc.format.extent |
2 p. |
es |
dc.title |
Shapes characterization on event address representation using histograms of oriented events and an extended LBP approach |
es |
uade.subject.descriptor |
Reconocimiento de Patrones |
es |
uade.subject.descriptor |
Sensores de Visión Dinámica |
es |
uade.proyecto.codigo |
P16T01 |
es |
uade.proyecto.nombre |
Segmentación de información visual a partir de cámaras retinianas: Aplicación a Robótica Móvil - Visita al Instituto de Microelectrónica de la Universidad de Sevilla |
es |
uade.area |
Alimentos / Biotecnología / Bioinformática |
es |
uade.proyecto.responsable |
Negri, Pablo |
|
uade.instituto |
Instituto de Tecnología |
es |