Efficient particle filtering using RANSAC with application to 3D face tracking
Image and Vision Computing
A new approach to estimating fundamental matrix
Image and Vision Computing
Overview of the CLEF 2009 robot vision track
CLEF'09 Proceedings of the 10th international conference on Cross-language evaluation forum: multimedia experiments
Overview of the CLEF 2009 robot vision track
CLEF'09 Proceedings of the 10th international conference on Cross-language evaluation forum: multimedia experiments
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For the submission from the University of Glasgow for the Image-CLEF 2009 Robot Vision Task a large set of interesting points were extracted using an edge corner detector, these points were used to represent each image. The RANSAC method [1] was then applied to estimate the similarity between test and training images based on the number of matched pairs of points. The location of robot was then annotated based on the training image which contains the highest number of matched point pairs with the test image. A set of decision rules with the respect to the trajectory behaviour of robot's motion were defined to refine the final results. An illumination filter was also applied for two of the runs in order to reduce the illumination effect.