Calibration between Depth and Color Sensors for Commodity Depth Cameras - Zhang, Cha; Zhang, Zhengyou (Computer Vision and Machine Learning with RGB-D Sensors, 2011)
Commodity depth cameras have created many interesting new applications in the research community recently. These applications often require the calibration information between the color and the depth cameras. Traditional checkerboard based calibration schemes fail to work well for the depth camera, since its corner features cannot be reliably detected in the depth image. In this paper, we present a maximum likelihood solution for the joint depth and color calibration based on two principles. First, in the depth image, points on the checkerboard shall be co-planar, and the plane is known from color camera calibration. Second, additional point correspondences between the depth and color images may be manually speci- fied or automatically established to help improve calibration accuracy. Uncertainty in depth values has been taken into account systematically. The proposed algorithm is reliable and accurate, as demonstrated by extensive experimental results on simulated and real-world examples