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This paper proposes a change detection approach, called FVA (feature vector analysis), for multi- resolution images, which is based on calculating the shape simi- larity
To handle outliers in training data, slack variables were intro- duced to SVMs (Cortes and Vapnik, 1995), which allow for a certain amount of feature vectors to be located on the
Connected component analysis: The detection of complex events in pedestrian groups is based on the pedestrian interaction graph which was constructed in the first layer.. The
Analogously to the 2D_line detector, the resulting lines are compared to the database objects to provide a decision about the correctness of a road object if the major part of
In contrast to these approaches which deal with pixel wise evi- dence to guide top-down methods, we propose to learn generic parts of facade objects to allow object categorization
A technique for automated face detection and its pose estimation using single image is developed. The algorithm includes: face detection, facial features
The main contribution of this paper is the use of point feature attributes to better segment MLS data into components that have a one-to-one relationship with objects. The
Andreoli and Yesou developed an approach based on the texture filtering (Andreoli and Yesou, 2007) and the detection of the change through the bands ratio (Andreoli and Yesou,
