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WP2: Evaluation, Integration and Standards
WP3: Visual Content Indexing
WP4: Content Description for Audio, Speech and Text
WP5: Multimodal Processing and Interaction
WP6: Machine Learning and Computation Applied to Multimedia
WP7: Dissemination towards Industry

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Home arrow News arrow Latest news arrow An Online Learning Framework
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
Detection and tracking

The VIDEO shows this integrated approach on faces.

  • Contact: Martina Uray, ICG ( This e-mail address is being protected from spam bots, you need JavaScript enabled to view it )  
  • For more background information, consult the MUSCLE Paper Archive : search for papers with MP-codes 217 and 262.