저널 : JICRS(Journal of Institute of Control, Robotics and Systems), Vol.21, No.11, pp.996-1002, 2015.
· 논문제목 : “Efficient 3D Scene Labeling using Object Detectors & Location Prior Maps”
· 저자 : 김주희, 김인철
· 요약 : 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.