Remote Sensing · 2015 · 210 citations · 36 references
EngineeringClose-range 3DField RoboticsRgb-d CamerasMulti-view Geometry3D Computer VisionImage AnalysisCalibrationCamera CalibrationKinematicsPermanent EvolutionComputational GeometryGeometric ModelingKinect V2 SensorMachine VisionRange ImagingComputer Vision3D VisionNatural Sciences3D ReconstructionRange Imaging CamerasRgb-d Camera
In the last decade, RGB-D cameras - also called range imaging cameras - have known a permanent evolution. Because of their limited cost and their ability to measure distances at a high frame rate, such sensors are especially appreciated for applications in robotics or computer vision. The Kinect v1 (Microsoft) release in November 2010 promoted the use of RGB-D cameras, so that a second version of the sensor arrived on the market in July 2014. Since it is possible to obtain point clouds of an observed scene with a high frequency, one could imagine applying this type of sensors to answer to the need for 3D acquisition. However, due to the technology involved, some questions have to be considered such as, for example, the suitability and accuracy of RGB-D cameras for close range 3D modeling. In that way, the quality of the acquired data represents a major axis. In this paper, the use of a recent Kinect v2 sensor to reconstruct small objects in three dimensions has been investigated. To achieve this goal, a survey of the sensor characteristics as well as a calibration approach are relevant. After an accuracy assessment of the produced models, the benefits and drawbacks of Kinect v2 compared to the first version of the sensor and then to photogrammetry are discussed.
36
KinectFusion: Real-time dense surface mapping and tracking
Richard A. Newcombe, Andrew Fitzgibbon, Shahram Izadi et al. · 2011 · 3.9K citations
Geometric Modeling, Accurate Real-time Mapping, Machine Vision +15
Real-time human pose recognition in parts from single depth images
Jamie Shotton, Toby Sharp, Alex Kipman et al. · Communications of the ACM · 2013 · 2K citations