We propose a simple and practical calibration technique that effectively estimates camera parameters from just five points on two orthogonal 1-D objects, each which has three collinear points, one of which is shared. We derive the basic equations needed to realize camera calibration from just five points observed on a single image that captures the objects. We describe a new camera calibration algorithm that estimates the camera parameters based on the basic equations and optimizes them by the bundle adjustment technique. Our method is validated by both computer simulated data and real images. The results show that the camera parameters yielded by our method are close to those yielded by existing methods. The tests demonstrate that our method is both effective and practical.

We describe an iterative stabilization method that can simultaneously recover camera motion and 3D shape from an image sequence captured under modest deviation from planar motion. This technique iteratively applies a factorization method based on planar motion and can approximate the observed image points to the 2D points projected under planar motion by stabilizing the camera motion. We apply the proposed method to aerial images acquired by a helicopter-borne camera and show better reconstruction of both motion and shape than Christy-Horaud's perspective factorization. Moreover, we confirm that the reprojection errors calculated from the recovered camera motion and 3D shape are very similar to the optimum results yielded by bundle adjustment.

We propose a practical method that realizes radiometric compensation based on direct and indirect light transports so that uncalibrated projector-camera systems can create desired image displays on 3D objects. By introducing compressed sensing, we efficiently construct the light transport matrix that includes direct/indirect light transports reflected from unknown 3D objects. Assuming that each camera pixel receives a linear summation of direct and indirect reflection lights via the color-mixing matrices, which are reformed by reference to the light transports, our proposed method adaptively compensates the color brightness output from the projector by controlling a feedback system. We demonstrate compensation trials that use reformed color-mixing matrices and confirm that our proposed method offers excellent projection-based displays on 3D objects.

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