2007 IEEE International Conference on Image Processing - San Antonio, Texas, U.S.A. - September 16-19, 2007

Technical Program

Paper Detail

Paper:TP-L2.4
Session:Image and Video Filtering and Multiresolution Processing
Time:Tuesday, September 18, 15:30 - 15:50
Presentation: Lecture
Title: TENSOR-BASED FILTER DESIGN USING KERNEL RIDGE REGRESSION
Authors: Christian Bauckhage; Deutsche Telekom Laboratories 
Abstract: Tensor-based approaches to visual object detection can drastically reduce the number of parameters in the training process. Compared to their vector-based counterparts, tensor methods therefore train faster, better manage noisy or corrupted training samples, and are less prone to over-fitting. In this paper, we show how to incorporate the kernel trick into tensor-based filter design. Dealing with object detection in cluttered natural environments, the method is shown to cope with substantially varying training data and a cascade of only two kernel tensor-filters is demonstrated to provide very reliable results.



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