Shapes characterization on event address representation using histograms of oriented events and an extended LBP approach

Negri, Pablo

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