Abstract: In this study, we have described an approach for a 3D scene reconstruction using 2 randomly selected adjacent colored video frames. We have used a single uncalibrated video camera to take a record for uncalibrated environment. The Selection of 2 frames based on the maximum homogeneity of points on these frames are favorable; could be any two adjacent frames. The use of Harris technique were very useful to find the edges and corners on each selected image (frame), then the use of the autocorrelation function based on Gaussian�s function been used to find the corresponding matched points. Then the correlated matched pair points are found on both images and by calculating the gradient of the correlated paired points on both images represents approximately the Z direction (calculating dzdx and dzdy). This is yielding that each point on each image (frame) can be represented in a 3D coordinates which yields to 3D shape estimation, which is achieved by the RANSAC function. This method has got an errors, because of its dependence on probability. The main advantages of the proposed approach is applicable for indoor and outdoor application. This technique is suiting the natural real world applications. The proposed method is illustrated on a set of examples of an indoor captured colored video records, the selected frames are selected randomly from the video records.
A.S.T. Hussain , N.E. Berrached , A.E. Murad and Tayeb Basta , 2006. 3D Shape Extraction from Uncalibrated Environments and Video Camera. Asian Journal of Information Technology, 5: 253-257.