@inproceedings{8c4ccfdfe36147958e563aac4acea931,
title = "Improved SIFT matching algorithm for 3D reconstruction from endoscopic images",
abstract = "SIFT (Scale Invariant Feature Transform) is wildly used in image matching but suffered from low matching pairs when employed in endoscope image. This paper presented an improved algorithm based on SIFT, the core contribution of which is Zone Matching approach. By collecting all feature points in a neighbor patch around the coordinate of an objective feature in the key image and finding the closest one to the feature in current image, the Zone Matching can obtain more matching pairs in shorter time. The experiment result shows a good improvement on the matching results both in matching number and computing time.",
keywords = "3D reconstruction, Endoscopy, Feature matching, Improved SIFT",
author = "Pengfei Du and Ya Zhou and Qiaona Xing and Xiaoming Hu",
year = "2011",
doi = "10.1145/2087756.2087864",
language = "English",
isbn = "9781450310604",
series = "Proceedings of VRCAI 2011: ACM SIGGRAPH Conference on Virtual-Reality Continuum and its Applications to Industry",
pages = "561--564",
booktitle = "Proceedings of VRCAI 2011",
note = "10th International Conference on Virtual Reality Continuum and Its Applications in Industry, VRCAI'11 ; Conference date: 11-12-2011 Through 12-12-2011",
}