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Efficient 3D Scene Labeling using Object Detectors & Location Prior Maps
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 Title & Authors
Efficient 3D Scene Labeling using Object Detectors & Location Prior Maps
Kim, Joo-Hee; Kim, In-Cheol;
 
 Abstract
In this paper, we present an effective system for the 3D scene labeling of objects from RGB-D videos. Our system uses a Markov Random Field (MRF) over a voxel representation of the 3D scene. In order to estimate the correct label of each voxel, the probabilistic graphical model integrates both scores from sliding window-based object detectors and also from object location prior maps. Both the object detectors and the location prior maps are pre-trained from manually labeled RGB-D images. Additionally, the model integrates the scores from considering the geometric constraints between adjacent voxels in the label estimation. We show excellent experimental results for the RGB-D Scenes Dataset built by the University of Washington, in which each indoor scene contains tabletop objects.
 Keywords
3D scene labeling;RGB-D video;Markov random field;object detection;location prior map;
 Language
Korean
 Cited by
 References
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