6533b82dfe1ef96bd12912fe
RESEARCH PRODUCT
Reliable Planar Object Pose Estimation in Light Fields From Best Subaperture Camera Pairs
Takuya FunatomiYasuhiro MukaigawaGuillaume CaronNathan Crombezsubject
Control and OptimizationComputer scienceProperty (programming)Biomedical EngineeringComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONSet (abstract data type)PlanarArtificial Intelligence[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]Computer visionPoseComputer Science::DatabasesGround truthbusiness.industryMechanical EngineeringAstrophysics::Instrumentation and Methods for Astrophysics[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]16. Peace & justiceObject (computer science)Computer Science ApplicationsHuman-Computer InteractionControl and Systems EngineeringComputer Science::Computer Vision and Pattern RecognitionComputer Vision and Pattern RecognitionArtificial intelligencebusinessdescription
International audience; A light-field camera can obtain richer information about a scene than a usual camera. This property offers a lot of potential for robot vision. In this paper, we present a method for pose estimation of a planar object with a light-field camera. The light-field camera can be regarded as a set of sub-aperture cameras. Although any combination of them can theoretically be used for the pose estimation, the accuracy depends on the combination. We show that the estimated pose error can be reduced by selecting the best pair of sub-aperture cameras. We have evaluated the accuracy of our approach with real experiments using a light-field camera in front of planar targets held by an industrial manipulator for ground truth comparison.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-10-01 |