Embedding images into a low dimensional space has a wide range of applications: visualization, clustering, and pre-processing for supervised learning. Traditional dimension reduct...
We present a new method to perform reliable matching between different images. This method finds complete region correspondences between concentric circles and the corresponding p...
Given two or more images, we can define different but related problems on pattern matching such as image registration, pattern detection and localization, and common pattern disco...
Robotic navigation algorithms increasingly make use of the panoramic field of view provided by omnidirectional images to assist with localization tasks. Since the images taken by ...
Nearest neighbor classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions due to the curse-ofdimensionality. Sev...