Hybrid tracking approach for assistive environments

Lalos, C; Anagnostopoulos, V; Konstanteli, K; Varvarigou, T

dc.contributor.author	Lalos, C	en
dc.contributor.author	Anagnostopoulos, V	en
dc.contributor.author	Konstanteli, K	en
dc.contributor.author	Varvarigou, T	en
dc.date.accessioned	2014-03-01T02:51:53Z
dc.date.available	2014-03-01T02:51:53Z
dc.date.issued	2009	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/35717
dc.subject	Computer Vision	en
dc.subject	IT Adoption	en
dc.subject	Machine Learning	en
dc.subject	Particle Filter	en
dc.subject	Patient Monitoring	en
dc.subject	Visual Tracking	en
dc.subject	Histograms of Oriented Gradients	en
dc.subject	Probabilistic Principal Component Analysis	en
dc.subject	rao blackwellized particle filter	en
dc.title	Hybrid tracking approach for assistive environments	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1145/1579114.1579178	en
heal.identifier.secondary	http://dx.doi.org/10.1145/1579114.1579178	en
heal.publicationDate	2009	en
heal.abstract	Camera based supervision is a critical component for patient monitoring in assistive environments. However, visual tracking still remains one of the biggest challenges in the area computer vision although it has been extensively studied during the previous decades. It this paper we propose a hybrid Rao -- Blackwellzed particle filter that combines two efficient, well-known tracking techniques with an innovative	en
heal.journalName	International Conference on Pervasive Technologies Related to Assistive Environments	en
dc.identifier.doi	10.1145/1579114.1579178	en