Direct 3D Information Determination in an Uncalibrated Stereovision System by Using Evolutionary Algorithms

Direct 3D Information Determination in an Uncalibrated Stereovision System by Using Evolutionary Algorithms

Alain Koch (Université de Bourgogne, France), Albert Dipanda (Université de Bourgogne, France) and Claire Bourgeois-République (Université de Bourgogne, France)
Copyright: © 2011 |Pages: 12
DOI: 10.4018/ijcvip.2011040103
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Abstract

This paper proposes a 3D panoramic shape reconstruction method based on an uncalibrated stereovision system (USS) composed of five cameras circularly located around the object to be analysed. First, some interesting points are detected from markers placed on the object such that they are visible by two successive cameras of the USS. These points are then matched on both images acquired by a couple of successive cameras. This process is repeated for all the couples of cameras. Second, by using an evolutionary algorithm, the depth values of the different interesting points are calculated. A comparison with a traditional method based on calibrated cameras validates the accuracy of 3D information provided by the proposed method. Finally, by combining all the interesting points, a panoramic view of the object is obtained.
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Background On The Epipolar Geometry

Usually the 3D reconstruction process requires a stereovision system composed of two or more cameras (Figure 1). The 3D coordinates are calculated by triangulation. The triangulation A REVOIR where is the cameras in the scene and the coordinates of point in each image. Usually, the pinhole camera model is used to calibrate cameras. In this purpose, the intrinsic and the extrinsic parameters must be calculated. The extrinsic parameters allow obtaining the transformation between a real point in the world system and its corresponding point in the camera system, while the transformation between the image plane and the camera system is provided by the intrinsic parameters. The intrinsic and extrinsic parameters must be calculated for each camera.

Figure 1.

Theoretical stereovision acquisition system

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