{'fraction_non_alphanumeric': 0.01352657004830918, 'fraction_numerical': 0.002898550724637681, 'mean_word_length': 5.058479532163743, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Camera Calibration Using Parallel Line Segments

In this paper, we propose a camera calibration method for surveillance cameras that uses the image projection of parallel 3D line segments of the same length. We assume that vertical line segments are perpendicular to the ground plane and their bottom end points are on the ground plane. Under this assumption, the camera parameters can be directly determined from at least two line segments without estimating vanishing points. By extending the minimal solution, we devise a closed-form solution to the least squares case with more than two line segments. Lens distortion is jointly optimized in bundle adjustment. Evaluation of synthetic data showed that the optimal depression angle of a camera is around 50 degrees. In real data evaluation, we used the joints of pedestrians as vertical line segments. The experimental results on public datasets showed that the proposed method used with a human pose detector can accurately calibrate wide-angle cameras that have radial distortion.