With the growing interest in object categorization various methods have emerged that perform well in this challenging task, yet are inherently limited to only a moderate number of...
The need to register data is abundant in applications such as: world modeling, part inspection and manufacturing, object recognition, pose estimation, robotic navigation, and reve...
Dimensionality reduction is an important problem in pattern recognition. There is a tendency of using more and more features to improve the performance of classifiers. However, not...
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
An interpretation system finds the likely mappings from portions of an image to real-world objects. An interpretation policy specifies when to apply which imaging operator, to whi...