Abstract
Three-dimensional (3D) reconstruction is one of the most attractive research topics in photogrammetry and computer vision. Nowadays 3D reconstruction with simple and consumable equipment plays an important role. In this paper, a 3D reconstruction desktop system is built based on binocular stereo vision using a laser scanner. The hardware requirements are a simple commercial hand-held laser line projector and two common webcams for image acquisition. Generally, 3D reconstruction based on passive triangulation methods requires point correspondences among various viewpoints. The development of matching algorithms remains a challenging task in computer vision. In our proposal, with the help of a laser line projector, stereo correspondences are established robustly from epipolar geometry and the laser shadow on the scanned object. To establish correspondences more conveniently, epipolar rectification is employed using Bouguet’s method after stereo calibration with a printed chessboard. 3D coordinates of the observed points are worked out with rayray triangulation and reconstruction outliers are removed with the planarity constraint of the laser plane. Dense 3D point clouds are derived from multiple scans under different orientations. Each point cloud is derived by sweeping the laser plane across the object requiring 3D reconstruction. The Iterative Closest Point algorithm is employed to register the derived point clouds. Rigid body transformation between neighboring scans is obtained to get the complete 3D point cloud. Finally polygon meshes are reconstructed from the derived point cloud and color images are used in texture mapping to get a lifelike 3D model. Experiments show that our reconstruction method is simple and efficient.
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