Bill Triggs

Polyhedral Conic Classifiers for Visual Object Detection and Classification

We propose a family of quasi-linear discriminants that outperform current large-margin methods in sliding window visual object detection and open set recognition tasks. In these tasks the classification problems are both numerically imbalanced -- positive (object class) training and test windows…