During the last decade of the twentieth century, computer vision made considerable progress towards the consolidation of its fundaments, in particular regarding the treatment of geometry for the evaluation of stereo image pairs and of multi-view image recordings. Scientists thus began to look at basic computer vision solutions - irrespective of the well-perceived need to perfection these further - as components which should be explored in a larger context. This volume is a post-event proceedings volume and contains selected papers based on the presentations given, and the lively discussions that ensued, during a seminar held in Dagstuhl Castle, Germany, in October 2003. Co-sponsored by ECVision, the cognitive vision network of excellence, it was organized to further strengthen cooperation between research groups from different countries, and scientists active in related areas were invited from around the world. The 18 thoroughly revised papers presented are organized in topical sections on foundations of cognitive vision systems, recognition and categorization, learning and adaptation, representation and inference, control and systems integration, and conclusions.All the algorithms were implemented in Matlab 6 and run on the 2.4 GHz PC under Linux OS. ... The width of the RBF kernel which yields the best classification performance of the SVM classifier was used in this experiment (cf. Section 7.3.2).
|Title||:||Cognitive Vision Systems|
|Author||:||Hans-Hellmut Nagel, Henrik I. Christensen|
|Publisher||:||Springer Science & Business Media - 2006-06-27|