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
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Convex Optimization
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Automatic Panoramic Image Stitching using Invariant Features
International Journal of Computer Vision
Robust multi-view feature matching from multiple unordered views
Pattern Recognition
Fast topology estimation for image mosaicing using adaptive information thresholding
Robotics and Autonomous Systems
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Large area photo-mosaics are widely used in many different applications such as optical mapping, panorama creation and autonomous vehicle navigation. When the trajectory of the camera provides an overlap between non-consecutive images (closed-loop trajectory), it is essential to detect such events in order to get globally coherent mosaics. Recent advances in image matching methods allow for registering pairs of images in the absence of prior information on orientation, scale or overlap between images. Owing to this, recent batch mosaicing algorithms attempt to detect non-consecutive overlapping images using exhaustive matching of image pairs. This paper proposes the use of Observation Mutual Information as a criterion to evaluate the benefit of potential matches between pairs of images. This allows for ranking and ordering a list of potential matches in order to make the loop-closing process more efficient. In this paper, the Observation Mutual Information criterion is compared against other strategies and results are presented using underwater imagery.