Distortion Invariant Object Recognition in the Dynamic Link Architecture
IEEE Transactions on Computers
Contextual Priming for Object Detection
International Journal of Computer Vision
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Object Categorization Based on Kernel Principal Component Analysis of Visual Words
WACV '08 Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision
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This paper presents a method to estimate the position of object using contextual information. Although convention methods used only shape contextual information, color contextual information is also effective to describe scenes. Thus we use both shape and color contextual information. To estimate the object position from only contextual information, the Support Vector Regression is used. We choose the Pyramid Match Kernel which measures the similarity between histograms because our contextual information is described as histogram. When one kernel is applied to a feature vector which consists of color and shape, the similarity of each feature is not used effectively. Thus, kernels are applied to color and shape independently, and the weighted sum of the outputs of both kernels is used. We confirm that the proposed method outperforms conventional methods.