Improved SIFT matching algorithm for 3D reconstruction from endoscopic images

Authors:
Pengfei Du;Ya Zhou;Qiaona Xing;Xiaoming Hu
Affiliations:
Beijing Institute of Technology, Beijing, China;Beijing Institute of Technology, Beijing, China;Beijing Institute of Technology, Beijing, China;Beijing Institute of Technology, Beijing, China
Venue:
Proceedings of the 10th International Conference on Virtual Reality Continuum and Its Applications in Industry
Year:
2011

Citing 4
Cited 0

Scale & Affine Invariant Interest Point Detectors

International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
Speeded-Up Robust Features (SURF)

Computer Vision and Image Understanding
ASIFT: A New Framework for Fully Affine Invariant Image Comparison

SIAM Journal on Imaging Sciences

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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.