Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
Recursive Estimation of Motion, Structure, and Focal Length
IEEE Transactions on Pattern Analysis and Machine Intelligence
Interactive Construction of 3D Models from Panoramic Mosaics
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Modeling and Rendering Architecture from Photographs:
Modeling and Rendering Architecture from Photographs:
A paintbrush laser range scanner
Computer Vision and Image Understanding
A paintbrush laser range scanner
Computer Vision and Image Understanding
Revisiting the PnP Problem with a GPS
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
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We propose PALM - a Portable sensor-Augmented vision system for Large-scene Modeling. The system solves the problem of recovering large structures in arbitrary scenes from video streams taken by a sensor-augmented camera. Central to the solution method is the use of multiple constraints derived from GPS measurements, camera orientation sensor readings, and image features. The knowledge of camera orientation enhances computational efficiency by making a linear formulation of perspective ray constraints possible. The overall shape is constructed by merging smaller shape segments. Shape merging errors are minimized using the concept of shape hierarchy, which is realized through a "landmarking" technique. The features of the system include its use of a small number of images and feature points, its portability, and its low cost interface for synchronizing sensor measurements with the video stream. Example reconstructions of a football stadium and two large buildings are presented and these results are compared with the ground truth.