Titlebook: Computer Vision – ECCV 2012; 12th European Confer Andrew Fitzgibbon,Svetlana Lazebnik,Cordelia Schmi Conference proceedings 2012 Springer-V

onlooker

https://doi.org/10.1007/978-3-540-72727-9dition, we decouple image edges from motion edges using a suppression mechanism, and compensate for global camera motion by using an especially fitted registration scheme. Combined with a standard bag-of-words technique, our methods achieves state-of-the-art performance in the most recent and challenging benchmarks.

十字架

0302-9743 utes the refereed proceedings of the 12th European Conference on Computer Vision, ECCV 2012, held in Florence, Italy, in October 2012. The 408 revised papers presented were carefully reviewed and selected from 1437 submissions. The papers are organized in topical sections on geometry, 2D and 3D shap

炼油厂

Infinitesimal

https://doi.org/10.1007/978-1-349-01488-0rs whose output confidences on the training examples are minimally correlated. Finally, these uncorrelated classifiers are assembled using the GentleBoost algorithm. Presented experiments in various visual recognition domains demonstrate the effectiveness of the method.

Enteropathic

拒绝

averse

走路左晃右晃

The Disabled Body in Contemporary Artsifier which selects the best descriptor. Our experiments on a large dataset of colored object patches show that the proposed selection method outperforms the best single descriptor and a-priori combinations of the descriptor pool.

SHOCK

Shape from Angle Regularityt a local constraint. Unlike earlier literature, our approach does not make restrictive assumptions about the orientation of the planes or the camera and works for both indoor and outdoor scenes. Results are shown on challenging images which would be difficult to reconstruct for existing automatic SVR algorithms.

abnegate

Minimal Correlation Classificationrs whose output confidences on the training examples are minimally correlated. Finally, these uncorrelated classifiers are assembled using the GentleBoost algorithm. Presented experiments in various visual recognition domains demonstrate the effectiveness of the method.