Camera auto-calibration for complex scenes

In this paper, we propose a novel method for automatic camera calibration based on pedestrians' observations. Our proposed method is capable of estimating calibration parameters for complex scenes having more than one ground plane. Unlike existing methods that require time-consuming optimization step, our method uses real-time re-estimation step based on fuzzy logic while relaxing the assumption on the number of ground planes in the scene. Furthermore, we propose a dominant ground plane detection step for better calibration parameter estimation on complex scenes. To evaluate our proposed method, we run comprehensive testing using 5 different datasets covering varieties of calibration parameters and scene properties, we also conduct tests on a synthetic dataset for more detailed analysis. Test results show that our proposed method outperforms existing state-of-the-art methods in both performance accuracy and time complexity.