Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
Estimating Geospatial Trajectory of a Moving Camera
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Image Based Localization in Urban Environments
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Retrieving landmark and non-landmark images from community photo collections
Proceedings of the international conference on Multimedia
View Clustering of Wide-Baseline N-views for Photo Tourism
SIBGRAPI '11 Proceedings of the 2011 24th SIBGRAPI Conference on Graphics, Patterns and Images
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We propose an algorithm for detection of noisy GPS and magnetometer tags in wide-baseline camera views. Our algorithm neither needs densely sampled views nor does it need a single visually connected path through all the views in the dataset. We use vision-based estimates of mutual rotation and translation between cameras to compute a measure of confidence on the correctness of the associated GPS and magnetometer tags. The vision algorithm can find the epipolar geometry between two wide-baseline images without needing pre-specified correspondences. We have two versions of our approach; one that requires geometric pose estimation between all pairs of images and a faster version that uses a pre-filter based on photometric comparison of images to quickly reject non-overlapping views from further geometric consideration. We show qualitative and quantitative results on the Nokia Grand Challenge 2010 Dataset. We find that magnetometer readings are more accurate than GPS readings.