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Erschienen in:
2016 | OriginalPaper | Buchkapitel
Object Categorization from RGB-D Local Features and Bag of Words
verfasst von : Jesus Martínez-Gómez, Miguel Cazorla, Ismael García-Varea, Cristina Romero-González
Erschienen in: Robot 2015: Second Iberian Robotics Conference
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Object categorization from robot perceptions has become one of the most well-known problems in robotics. How to select proper representations for these perceptions, specially when using RGB-D images, has received a significant attention in the last years. We present in this paper an object categorization approach from RGB-D images. This approach is based on the BoW representation, and it allows to integrate any type of 3D local feature implemented in the Point Cloud Library. The experimentation performed over the challenging RGB-D Object dataset shows how competitive object categorization systems can be developed using this procedure.