A Dynamic Depth Extraction Method (DDEM) is proposed, which measures the time required for an edge to move through a known distance on the image plane and hence is able to calculate depth. Experimental results for three vertical bars in different depths show that the mean depths obtained by DDEM were almost the same as those obtained from direct measurement. The fluctuation of obtained depth was about 3.6%, which corresponds to one half frame difference in matching time of the near bar. Three kins of thresholds (λ1, λ2 and λ3) were introduced to reduce the noise affection. There was a wide range of thresholds for which the depth can be extracted stably. The DDEM was also successfully applied to recovering 3D structure of a complicated room.

We propose a method for camera calibration based on image registration. This method registers two images; one is a real image captured by a camera with a calibration object with known shape and texture, and the other is a synthetic image containing the object. The proposed method estimates the parameters of the rotation and translation of the object by using the depth information of the synthetic image. The Gauss-Newton method is used to minimize the residuals of intensities of the two images. The proposed method does not depend on initial values of the minimization, and is applicable to images with much noise. Experimental results using real images demonstrate the robustness against initial state and noise on the image.