| An Online Learning Framework |
for Object Detection, Tracking and Recognition. ICG (TU Graz) have developed a novel framework for object detection, tracking and recognition. Unlike other approaches we are interested in a seamless integration of these modules. Detection and tracking is done with our online AdaBoost algorithm, based on Haar wavelets and local orientation histograms, while recognition is done with our fast approximated SIFT descriptor. We use a common over-complete representation which is shared by the different modules. By means of the integral data structure the features are real-time computable enabling a real-time implementation of all three modules. The common feature pool enables the integration of detection, tracking and recognition not only on the module level, but also on the feature level which in turn facilitates the robustness and opens new venues of module interaction.
 Detection and tracking The VIDEO shows this integrated approach on faces.
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