A real-time fisheye video correction method based on Android smart-phone GPU

We propose a fisheye camera calibration algorithm, in which the center of the distortion and equivalent focal length of the fisheye camera are obtained by the contour constraint, and the distortion parameters are calculated by linear constraint and Levenberg-Marquardt (LM) optimization algorithm. According to the obtained camera parameters, the fisheye image can be corrected by cubic-box-mapping-method (CBMM). The result shows that for checkerboard images the calibration algorithm demonstrates a high-accuracy of about 0.6727 pixels in the average reprojection root-mean-square error (RMSE). Based on the calibration algorithm, the ream-time fisheye video correction is implemented on an android smart-phone. In the implementation, a direct mapping method is used to simplify the cubic box mapping method, and a heterogeneous architecture with a graphics processing unit (GPU) is built to accelerate the algorithm. Lastly, a fisheye video stream of 1280 x 1280 resolution is timely corrected on the smart-phone with a speed of 25 frames/sec.