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In this work, we developed a multimodal imaging system for real-time applications by integrating 2D image sensors in different spectral ranges as well as a polarization camera into a high-speed optical 3D sensor. For the generation of the multimodal image data, a pixel-level alignment of 2D images in different modalities to 3D data is realized by applying projection matrices to each point in the 3D point cloud. For the calculation of projection matrices for each 2D image sensor, a calibration procedure is proposed for the extrinsic calibration of arbitrarily positioned image sensors. The final imaging system delivers multimodal video data with one mega-pixel resolution at a frame rate of 30 Hz. As application examples, we demonstrate the estimation of vital signs and the detection of human body parts with this imaging system.
Rosenberger et al. (Tue,) studied this question.