ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Multiple view geometry in computer visiond
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ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
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CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
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Computer Vision and Image Understanding - Special isssue on video retrieval and summarization
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International Journal of Computer Vision
Effective image and video mining: an overview of model-based approaches
MDM '05 Proceedings of the 6th international workshop on Multimedia data mining: mining integrated media and complex data
The Pyramid Match Kernel: Efficient Learning with Sets of Features
The Journal of Machine Learning Research
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Flexible Spatial Configuration of Local Image Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Organizing rushes video by visually similar setting
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
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Computer Vision and Image Understanding
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Image and Vision Computing
Video shots retrieval using local invariant features
IMCE '09 Proceedings of the 1st international workshop on Interactive multimedia for consumer electronics
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MCAM'07 Proceedings of the 2007 international conference on Multimedia content analysis and mining
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CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
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We describe progress in matching shots which are images of the same 3D scene in a film. The problem is hard because the camera viewpoint may change substantially between shots, with consequent changes in the imaged appearance of the scene due to foreshortening, scale changes and partial occlusion.We demonstrate that wide baseline matching techniques can be successfully employed for this task by matching key frames between shots. The wide baseline method represents each frame by a set of viewpoint invariant local feature vectors. The local spatial support of the features means that segmentation of the frame (e.g. into foreground/background) is not required, and partial occlusion is tolerated.Results of matching shots for a number of different scene types are illustrated on a commercial film.