IEEE Transactions on Pattern Analysis and Machine Intelligence
3D Photography Using Shadows in Dual-Space Geometry
International Journal of Computer Vision
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Good Features to Track
High-Quality Real-Time Stereo Using Adaptive Cost Aggregation and Dynamic Programming
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Laser brush: a flexible device for 3D reconstruction of indoor scenes
Proceedings of the 2008 ACM symposium on Solid and physical modeling
SBA: A software package for generic sparse bundle adjustment
ACM Transactions on Mathematical Software (TOMS)
Parallel Tracking and Mapping for Small AR Workspaces
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Shape reconstruction and texture sampling by active rectification and virtual view synthesis
Computer Vision and Image Understanding
Editor's Choice Article: Video-based, real-time multi-view stereo
Image and Vision Computing
RSLAM: A System for Large-Scale Mapping in Constant-Time Using Stereo
International Journal of Computer Vision
Low-Cost laser range scanner and fast surface registration approach
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
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We present a tool for the acquisition of 3D textured models of objects of desktop size using an hybrid computer vision framework. This framework combines active laser-based triangulation with passive motion estimation. The 3D models are obtained by motion-based alignment (with respect to a fixed world frame) of imaged laser profiles backprojected onto time-varying camera frames. Two distinct techniques for estimating camera displacements are described and evaluated. The first is based on a Simultaneous Localization and Mapping (SLAM) approach, while the second exploits a planar pattern in the scene and recovers motion by homography decomposition. Results obtained with a custom laser-camera stereo setup -- implemented with off-the-shelf hardware -- show that a trade-off exists between the greater operational flexibility of SLAM and the higher model accuracy of the homography-based approach.