ACCURACY TEST OF MICROSOFT KINECT FOR HUMAN MORPHOLOGIC MEASUREMENTS

Article, Other literature type English OPEN
B. Molnár ; C. K. Toth ; A. Detrekői (2012)
  • Publisher: Copernicus Publications
  • Journal: The International Archives of the Photogrammetry (issn: 1682-1750, eissn: 2194-9034)
  • Related identifiers: doi: 10.5194/isprsarchives-XXXIX-B3-543-2012
  • Subject: TA1-2040 | T | TA1501-1820 | Applied optics. Photonics | Engineering (General). Civil engineering (General) | Technology
    acm: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION

The Microsoft Kinect sensor, a popular gaming console, is widely used in a large number of applications, including close-range 3D measurements. This low-end device is rather inexpensive compared to similar active imaging systems. The Kinect sensors include an RGB camera, an IR projector, an IR camera and an audio unit. The human morphologic measurements require high accuracy with fast data acquisition rate. To achieve the highest accuracy, the depth sensor and the RGB camera should be calibrated and co-registered to achieve high-quality 3D point cloud as well as optical imagery. Since this is a low-end sensor, developed for different purpose, the accuracy could be critical for 3D measurement-based applications. Therefore, two types of accuracy test are performed: (1) for describing the absolute accuracy, the ranging accuracy of the device in the range of 0.4 to 15 m should be estimated, and (2) the relative accuracy of points depending on the range should be characterized. For the accuracy investigation, a test field was created with two spheres, while the relative accuracy is described by sphere fitting performance and the distance estimation between the sphere center points. Some other factors can be also considered, such as the angle of incidence or the material used in these tests. The non-ambiguity range of the sensor is from 0.3 to 4 m, but, based on our experiences, it can be extended up to 20 m. Obviously, this methodology raises some accuracy issues which make accuracy testing really important.