Virtual Calibration Pattern Realization for HybridFOV Multiview Calibration * Multiview vision systems are commonly applied in different fields at present, including hybridfieldofview(hybridFOV) multiview systems. The difference between camerasxe2x80x99 FOVs results in the difficulty of calibration, such as lack of information for cameras with small FOVs. All the information acquired by the other cameras and the projective geometry between them should be utilized in camera calibration. In this paper, a method of generating redundant constraints with trifocal tensor and the information from the cameras with a large FOV is proposed. The process is described after some reminders of trilinearities. Then, two simulated experiments based on this method have been implemented. The results and analysis show the feasibility of this method.

View interpolation by inverse filtering : Generating the center view using multiview images of circular camera array This paper deals with a view interpolation problem using multiple images captured with a circular camera array. An inverse filtering method for reconstructing a virtual image at the center of the camera array is proposed. First, we generate a candidate image by adding all correspondence pixel values based on multiple layers assumed in a scene. Second, we model a linear relationship between the desired virtual image and the candidate image, and then derive the inverse filter to reconstruct the virtual image. Since we can derive the inverse filter independent of the scene structure, the proposed method requires no depth estimation. Simulation results using synthetic images show that increasing the number of cameras and layers improves the quality of the virtual image.