...
首页> 外文期刊>Sensors >A Quantitative Comparison of Calibration Methods for RGB-D Sensors Using Different Technologies
【24h】

A Quantitative Comparison of Calibration Methods for RGB-D Sensors Using Different Technologies

机译:使用不同技术的RGB-D传感器校准方法的定量比较

获取原文
           

摘要

RGB-D ( Red Green Blue and Depth ) sensors are devices that can provide color and depth information from a scene at the same time. Recently, they have been widely used in many solutions due to their commercial growth from the entertainment market to many diverse areas (e.g., robotics, CAD, etc.). In the research community, these devices have had good uptake due to their acceptable levelofaccuracyformanyapplicationsandtheirlowcost,butinsomecases,theyworkatthelimitof their sensitivity, near to the minimum feature size that can be perceived. For this reason, calibration processes are critical in order to increase their accuracy and enable them to meet the requirements of such kinds of applications. To the best of our knowledge, there is not a comparative study of calibration algorithms evaluating its results in multiple RGB-D sensors. Speci?cally, in this paper, a comparison of the three most used calibration methods have been applied to three different RGB-D sensors based on structured light and time-of-?ight. The comparison of methods has been carried out by a set of experiments to evaluate the accuracy of depth measurements. Additionally, an object reconstruction application has been used as example of an application for which the sensor works at the limit of its sensitivity. The obtained results of reconstruction have been evaluated through visual inspection and quantitative measurements.
机译:RGB-D(红色,绿色,蓝色和深度)传感器是可以同时提供场景中颜色和深度信息的设备。近年来,由于它们从娱乐市场到许多不同领域(例如,机器人技术,CAD等)的商业增长,它们已被广泛用于许多解决方案中。在研究界中,由于这些设备在任何应用中都具有可接受的精度水平,并且成本较低,因此具有良好的吸收能力,但是在某些情况下,它们在其灵敏度范围内工作,接近可以感知的最小特征尺寸。因此,为了提高校准精度并使其满足此类应用的要求,校准过程至关重要。据我们所知,目前还没有对校准算法在多个RGB-D传感器中评估其结果的比较研究。具体而言,在本文中,已将三种最常用的校准方法的比较应用于基于结构光和行进时间的三种不同的RGB-D传感器。方法的比较已通过一组实验进行,以评估深度测量的准确性。另外,对象重建应用程序已被用作传感器在其灵敏度极限下工作的应用程序示例。通过目视检查和定量测量对获得的重建结果进行了评估。

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号