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Efficient 3D object detection using multiple pose-specific classifiers

AuthorsVillamizar, Michael ; Grabner, Helmut; Moreno-Noguer, Francesc ; Andrade-Cetto, Juan ; Gool, Luc van; Sanfeliu, Alberto
Issue Date2011
PublisherBritish Machine Vision Association
CitationProceedings of the British Machine Vision Conference: 20.1-20.10 (2011)
AbstractWe 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.
DescriptionPresentado al 22nd BMVC celebrado en University of Dundee (Escocia) en septiembre de 2011.
Publisher version (URL)http://dx.doi.org/10.5244/C.25.20
Identifiersdoi: 10.5244/C.25.20
Appears in Collections:(IRII) Libros y partes de libros
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