A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Object modelling by registration of multiple range images
Image and Vision Computing - Special issue: range image understanding
Iterative point matching for registration of free-form curves and surfaces
International Journal of Computer Vision
The digital Michelangelo project: 3D scanning of large statues
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Constraint-Based Sensor Planning for Scene Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Video Mosaicing through Topology Inference and Local to Global Alignment
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
A Solution for the Registration of Multiple 3D Point Sets Using Unit Quaternions
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Automatic three-dimensional modeling from reality
Automatic three-dimensional modeling from reality
Registration of point cloud data from a geometric optimization perspective
Proceedings of the 2004 Eurographics/ACM SIGGRAPH symposium on Geometry processing
Alignment of Continuous Video onto 3D Point Clouds
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fully Automatic Registration of 3D Point Clouds
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
The Great Buddha Project: Digitally Archiving, Restoring, and Analyzing Cultural Heritage Objects
International Journal of Computer Vision
International Journal of Computer Vision
International Journal of Computer Vision
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Multiview registration for large data sets
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
Flexible calibration of structured-light systems projecting point patterns
Computer Vision and Image Understanding
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We are currently developing a vision-based system aiming to perform a fully automatic pipeline for in situ photorealistic three-dimensional (3D) modeling of previously unknown, complex and unstructured underground environments. Since in such environments navigation sensors are not reliable, our system embeds only passive (camera) and active (laser) 3D vision senors. Laser Range Finders are particularly well suited for generating dense 3D maps by aligning multiples scans acquired from different viewpoints. Nevertheless, nowadays Iteratively Closest Point (ICP)-based scan matching techniques rely on heavy human operator intervention during a post-processing step. Since a human operator cannot access the site, these techniques are not suitable in high-risk underground environments. This paper presents an automatic on-line scan matcher able to cope with the nowadays 3D laser scanners' architecture and to process either intensity or depth data to align scans, providing robustness with respect to the capture device. The proposed implementation emphasizes the portability of our algorithm on either single or multi-core embedded platforms for on-line mosaicing onboard 3D scanning devices. The proposed approach addresses key issues for in situ 3D modeling in difficult-to-access and unstructured environments and solves for the 3D scan matching problem within an environment-independent solution. Several tests performed in two prehistoric caves illustrate the reliability of the proposed method.