Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluation of Features Detectors and Descriptors based on 3D Objects
International Journal of Computer Vision
Modeling the World from Internet Photo Collections
International Journal of Computer Vision
ASIFT: A New Framework for Fully Affine Invariant Image Comparison
SIAM Journal on Imaging Sciences
Computer
A comparative evaluation of interest point detectors and local descriptors for visual SLAM
Machine Vision and Applications
PCA-SIFT: a more distinctive representation for local image descriptors
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Evaluation of Interest Point Detectors and Feature Descriptors for Visual Tracking
International Journal of Computer Vision
A comparative evaluation of feature detectors on historic repeat photography
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part II
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We present the first step of the Rheims city (France) 3D reconstruction based on old postcards. Rheims endured drastic destruction during the First and then the Second World Wars. Old postcards, embodying the period from the beginning to the end of the 20th century, establish a testimony of the evolution in time and space of the most important places and monuments in the city. We aim to localize, render and visualize in 3D the buildings of this city, by using this sparse dataset and incomplete cadastral surveys. Image matching is initially required for locating a building in the city space. In this paper we propose a performance comparison of state-of-the-art detector-descriptor couples. We focus on their robustness and their transformations invariance when low resolution data is subject to temporal and space modifications.