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Efficient 3D object detection using multiple pose-specific classifiers
Villamizar Vergel, Michael Alejandro; Grabner, Helmut; Andrade-Cetto, Juan; Sanfeliu Cortés, Alberto; Van Gool, Luc; Moreno-Noguer, Francesc
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Universitat Politècnica de Catalunya. Institut de Robòtica i Informàtica Industrial; Universitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel.ligents
We propose an efficient method for object localization and 3D pose estimation. A two-step approach is used. In the first step, a pose estimator is evaluated in the input images in order to estimate potential object locations and poses. These candidates are then validated, in the second step, by the corresponding pose-specific classifier. The result is a detection approach that avoids the inherent and expensive cost of testing the complete set of specific classifiers over the entire image. A further speedup is achieved by feature sharing. Features are computed only once and are then used for evaluating the pose estimator and all specific classifiers. The proposed method has been validated on two public datasets for the problem of detecting of cars under several views. The results show that the proposed approach yields high detection rates while keeping efficiency.
Àrees temàtiques de la UPC::Enginyeria electrònica i telecomunicacions::Processament del senyal::Processament de la imatge i del senyal vídeo
Computer vision
computer vision
Visió per ordinador
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/publishedVersion
info:eu-repo/semantics/conferenceObject
         

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