Abstract
We present a novel method of geometric calibration of micro-lens-based light-field cameras. Accurate geometric calibration is a basis of various applications. Instead of using sub-aperture images, we utilize raw images directly for calibration. We select proper regions in raw images and extract line features from micro-lens images in those regions. For the whole process, we formulate a new projection model of micro-lens-based light-field cameras. It is transformed into a linear form using line features. We compute an initial solution of both intrinsic and extrinsic parameters by a linear computation, and refine it via a non-linear optimization. Experimental results show the accuracy of the correspondences between rays and pixels in raw images, estimated by the proposed method.
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Bok, Y., Jeon, HG., Kweon, I.S. (2014). Geometric Calibration of Micro-Lens-Based Light-Field Cameras Using Line Features. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds) Computer Vision – ECCV 2014. ECCV 2014. Lecture Notes in Computer Science, vol 8694. Springer, Cham. https://doi.org/10.1007/978-3-319-10599-4_4
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DOI: https://doi.org/10.1007/978-3-319-10599-4_4
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