Hyunsuk Ko, Han Suk Shim, Ouk Choi and C.-C. Jay Kuo. MCL-SS: “Robust uncalibrated stereo rectification with constrained geometric distortions (USR-CGD).” in Image and Vision Computing, vol. 60, pp. 98-114. 2017. PDF
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Contact Info: Hyunsuk Ko (email@example.com)
MCL-SS consists of four synthetic stereo image pairs generated by OpenGL programming, which are shown in Fig. 1. The advantage of using a synthetic image is that several geometric distortions can be easily applied to left and right images.
Assuming that two cameras are initially set as shown in Fig. 2, we can translate or rotate each of cameras along X-/Y-/Z-axes. This allows us to mimic some real camera configurations. For example, for the rotational geometric distortion, we can emulate converged camera setup by rotating two cameras on Y-axis in the opposite direction. For the translational distortion, we can also imitate wide baseline, vertical misalignment, and different zoom levels by moving two cameras on X-/Y-/Z-axes, respectively. Also, we can apply all the six distortions together.
For each of original synthetic stereo image pairs, we generate eight test stereo pairs, where six of them are obtained by applying single geometric distortion while the other two are generated by applying all the six geometric distortions together. As an example, a set of test images with different geometric distortion is demonstrated in Fig. 3~Fig. 5. Concretely, we move left and right cameras along X & Y axes and the range of increased disparity is 0~185 pixels. The ratio of object’s sizes between left and right images due to the cameras’ translation on Z-axis is about 11.98%~31.24%. Finally, the angle difference due to the camera rotation is 10˚on each axis.
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Fig. 1 Four reference image pairs
Fig. 2 Camera configuration for acquiring synthetic stereo images
Fig. 3 Rotation Distortion
Fig. 4 Translation Distortion
Fig. 5 Compound Distortion