The nature of statistical learning theory
The nature of statistical learning theory
Support Vector Machines for 3D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Choosing Multiple Parameters for Support Vector Machines
Machine Learning
Combining Evidence in Multimodal Personal Identity Recognition Systems
AVBPA '97 Proceedings of the First International Conference on Audio- and Video-Based Biometric Person Authentication
Mean Shift Analysis and Applications
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Face recognition: component-based versus global approaches
Computer Vision and Image Understanding - Special issue on Face recognition
The Amsterdam Library of Object Images
International Journal of Computer Vision
An information systems security risk assessment model under uncertain environment
Applied Soft Computing
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A new method for image object recognition is proposed. The complicated relation between the visual features and the recognizing result are modeled using evidence theory in the proposed method. Given a recognition task, new method constructs multiple SVMs each for a single feature, and then a modified combination rule is utilized to fuse initial results from multiple SVMs to a more reliable result as the initial results often conflict with each other. In this way, the influence of different features is tuned properly, thus the system may adapt itself to different recognition tasks. Experiments demonstrate the effectiveness of the proposed method.