Implementing discrete mathematics: combinatorics and graph theory with Mathematica
Implementing discrete mathematics: combinatorics and graph theory with Mathematica
Creating full view panoramic image mosaics and environment maps
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
True Multi-Image Alignment and Its Application to Mosaicing and Lens Distortion Correction
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Video Mosaicing through Topology Inference and Local to Global Alignment
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Propagating Covariance in Computer Vision
Proceedings of the Theoretical Foundations of Computer Vision, TFCV on Performance Characterization in Computer Vision
Bundle Adjustment - A Modern Synthesis
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Mosaics of Scenes with Moving Objects
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
A Graph-Based Global Registration for 2D Mosaics
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Image Mosaicing and Super-Resolution (Cphc/Bcs Distinguished Dissertations.)
Image Mosaicing and Super-Resolution (Cphc/Bcs Distinguished Dissertations.)
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Automatic Panoramic Image Stitching using Invariant Features
International Journal of Computer Vision
Visually Mapping the RMS Titanic: Conservative Covariance Estimates for SLAM Information Filters
International Journal of Robotics Research
On the History of the Minimum Spanning Tree Problem
IEEE Annals of the History of Computing
A New Global Alignment Method for Feature Based Image Mosaicing
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Fast image blending using watersheds and graph cuts
Image and Vision Computing
Match Selection in Batch Mosaicing Using Mutual Information
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
Fast and robust photomapping with an unmanned aerial vehicle (UAV)
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Information-based compact pose SLAM
IEEE Transactions on Robotics
Journal of Field Robotics - Visual Mapping and Navigation Outdoors
Efficient View-Based SLAM Using Visual Loop Closures
IEEE Transactions on Robotics
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Over the past decade, several image mosaicing methods have been proposed in robotic mapping and remote sensing applications. Owing to rapid developments in obtaining optical data from areas beyond human reach, there is a high demand from different science fields for creating large-area image mosaics, often using images as the only source of information. One of the most important steps in the mosaicing process is motion estimation between overlapping images to obtain the topology, i.e., the spatial relationships between images. In this paper, we propose a generic framework for feature-based image mosaicing capable of obtaining the topology with a reduced number of matching attempts and of getting the best possible trajectory estimation. Innovative aspects include the use of a fast image similarity criterion combined with a Minimum Spanning Tree (MST) solution, to obtain a tentative topology and information theory principles to decide when to update trajectory estimation. Unlike previous approaches for large-area mosaicing, our framework is able to naturally deal with the cases where time-consecutive images cannot be matched successfully, such as completely unordered sets. This characteristic also makes our approach robust to sensor failure. The performance of the method is illustrated with experimental results obtained from different challenging underwater image sequences.