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FINDDD: A fast 3D descriptor to characterize textiles for robot manipulation
Ramisa Ayats, Arnau; Alenyà Ribas, Guillem; Moreno-Noguer, Francesc; Torras, Carme
Universitat Politècnica de Catalunya. Institut de Robòtica i Informàtica Industrial; Universitat Politècnica de Catalunya. ROBiri - Grup de Robòtica de l'IRI; Universitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel.ligents
Most current depth sensors provide 2.5D range images in which depth values are assigned to a rectangular 2D array. In this paper we take advantage of this structured information to build an efficient shape descriptor which is about two orders of magnitude faster than competing approaches, while showing similar performance in several tasks involving deformable object recognition. Given a 2D patch surrounding a point and its associated depth values, we build the descriptor for that point, based on the cumulative distances between their normals and a discrete set of normal directions. This processing is made very efficient using integral images, even allowing to compute descriptors for every range image pixel in a few seconds. The discriminative power of our descriptor, dubbed FINDDD, is evaluated in three different scenarios: recognition of specific cloth wrinkles, instance recognition from geometry alone, and detection of reliable and informed grasping points.
Peer Reviewed
Àrees temàtiques de la UPC::Informàtica::Robòtica
Computer vision
computer vision feature extraction Author keywords: 3D descriptor
range image
real-time features Projectes: s'hauria de corregir el segon ítem
que inclou dos projectes: INtellact i VISen. Jo he probat de crear ViSen per separat
però no apareix com creat (?)
Robòtica
Classificació INSPEC::Pattern recognition::Computer vision
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/submittedVersion
info:eu-repo/semantics/conferenceObject
Institute of Electrical and Electronics Engineers (IEEE)
         

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