Pagliari Diana, Pinto Livio
Politecnico di Milano, Department of Civil and Environmental Engineering (DICA)-Geomatic and Geodesy Section, Piazza Leonardo da Vinci 32, 20133 Milan, Italy.
Sensors (Basel). 2015 Oct 30;15(11):27569-89. doi: 10.3390/s151127569.
In recent years, the videogame industry has been characterized by a great boost in gesture recognition and motion tracking, following the increasing request of creating immersive game experiences. The Microsoft Kinect sensor allows acquiring RGB, IR and depth images with a high frame rate. Because of the complementary nature of the information provided, it has proved an attractive resource for researchers with very different backgrounds. In summer 2014, Microsoft launched a new generation of Kinect on the market, based on time-of-flight technology. This paper proposes a calibration of Kinect for Xbox One imaging sensors, focusing on the depth camera. The mathematical model that describes the error committed by the sensor as a function of the distance between the sensor itself and the object has been estimated. All the analyses presented here have been conducted for both generations of Kinect, in order to quantify the improvements that characterize every single imaging sensor. Experimental results show that the quality of the delivered model improved applying the proposed calibration procedure, which is applicable to both point clouds and the mesh model created with the Microsoft Fusion Libraries.
近年来，随着创建沉浸式游戏体验的需求不断增加，手势识别和运动跟踪技术的巨大进步成为了电子游戏行业的一大特征。微软Kinect传感器能够以高帧率采集RGB、红外和深度图像。由于所提供信息具有互补性，它已被证明是吸引背景各异的研究人员的一项资源。2014年夏季，微软基于飞行时间技术在市场上推出了新一代Kinect。本文提出了针对Xbox One成像传感器的Kinect校准方法，重点关注深度相机。已估算出将传感器所犯误差描述为传感器自身与物体之间距离的函数的数学模型。这里呈现的所有分析均针对两代Kinect进行，以便量化每个成像传感器的改进之处。实验结果表明，应用所提出的校准程序可提高所提供模型的质量，该程序适用于点云以及使用微软融合库创建的网格模型。
