Time of Flight Cameras : Principles , Methods , and Applications

Abstract

Severalmethods that combine range and color data have been investigated and successfully used in various applications.Most of these systems suffer from the problems of noise in the range data and resolutionmismatch between the range sen- sor and the color cameras. High-resolution depth maps can be obtained using stereo matching, but this often fails to construct accurate depthmaps of weakly/repetitively textured scenes. Range sensors provide coarse depth information regardless of pres- ence/absence of texture.We propose a novel tof-stereo fusion method based on an efficient seed-growing algorithm which uses the tof data projected onto the stereo image pair as an initial set of correspondences. These initial “seeds” are then prop- agated to nearby pixels using a matching score that combines an image similarity criterion with rough depth priors computed from the low-resolution range data. The overall result is a dense and accurate depthmap at the resolution of the color cameras at hand. We show that the proposed algorithm outperforms 2D image-based stereo algorithms and that the results are of higher resolution than off-the-shelf RGB-D sensors, e.g., Kinect.