Automatic Panorama Recognition and Stitching Based on Graph Structure
Yi-Li Zhao, Yan Xia
Available Online July 2013.
- https://doi.org/10.2991/cse.2013.58How to use a DOI?
- feature detection; feature matching; image recognition; image matching; image stitching
- An automatic panorama recognition and stitching method based on graph structure was proposed to solve the multiple images recognition and matching problem. With multiple unordered images of user input, the method can automatically finding overlapping portion between images, and stitch them. First, the MOPS feature points were detected from the input images, and using kd-tree nearest neighbor search to perform fast feature matching between images. The motion model between any two images can be established by RANSAC algorithm based on the correspondence of feature points, and robust verification by a probabilistic algorithm. The automatic recognition of multiple panoramic images problem can be solved by building undirected connected graph corresponding to image matching relationship. Finally, a recursive algorithm was used to do depth-first traversal of the established undirected connected graphs, and multi-band blending algorithm was used to eliminate stitching seam. The experiments showed that multiple unordered images can be matched and recognized automatically, and panoramas can also be stitched automatically and seamlessly.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yi-Li Zhao AU - Yan Xia PY - 2013/07 DA - 2013/07 TI - Automatic Panorama Recognition and Stitching Based on Graph Structure BT - 2nd International Conference on Advances in Computer Science and Engineering (CSE 2013) PB - Atlantis Press SP - 261 EP - 263 SN - 1951-6851 UR - https://doi.org/10.2991/cse.2013.58 DO - https://doi.org/10.2991/cse.2013.58 ID - Zhao2013/07 ER -