We present a component-based system for object detection and identification. From a set of training images of a given object we extract a large number of components which are clust...
Bernd Heisele, Ivaylo Riskov, Christian Morgenster...
Training datasets for object detection problems are typically very large and Support Vector Machine (SVM) implementations are computationally complex. As opposed to these complex ...
The visual detection and recognition of objects is facilitated by context. This paper studies two types of learning methods for realizing context-based object detection in paintin...
Niek Bergboer, Eric O. Postma, H. Jaap van den Her...
This paper describes a method to minimize the immense training time of the conventional Adaboost learning algorithm in object detection by reducing the sampling area. A new algorit...
Florian Baumann, Katharina Ernst, Arne Ehlers, Bod...
Most multi-camera systems assume a well structured environment to detect and track objects across cameras. Cameras need to be fixed and calibrated, or only objects within a traini...
Alexandre Alahi, Pierre Vandergheynst, Michel Bier...