Kinect-style (or Depth) cameras use both an RGB and a depth sensor that acquire color and per-pixel depth data (depth-map), respectively. Due to their aﬀordable price and rich data they provide, depth cameras are being extensively used on research in assistive environments. Most of the robotic and computer-vision systems that use these Kinectstyle cameras require an accurate knowledge of the cameracalibration parameters. Traditional calibration methods, e.g., those that use a checker-board pattern, cannot be straightforwardly used to calibrate the Kinect-style cameras since the depth sensor can not distinguish patterns. Several calibration methods have emerged that try to calibrate depth cameras. In this paper, we present a comparative study of some of the most important Kinect-sytle calibration algorithms. Our work includes an implementation of these methods along with a comparison of their performance in both simulation and real-world experiments.
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