Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Efficient 3D Scene Labeling using Object Detectors & Location Prior Maps

물체 탐지기와 위치 사전 확률 지도를 이용한 효율적인 3차원 장면 레이블링

  • Kim, Joo-Hee (Artificial Intelligence Laboratory, Kyonggi University) ;
  • Kim, In-Cheol (Artificial Intelligence Laboratory, Kyonggi University)
  • 김주희 (경기대학교 컴퓨터과학과 인공지능연구실) ;
  • 김인철 (경기대학교 컴퓨터과학과 인공지능연구실)
  • Received : 2015.08.24
  • Accepted : 2015.10.22
  • Published : 2015.11.01
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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.

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References

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