We present a framework for learning object representations for fast recognition of a large number of different objects. Rather than learning and storing feature representations s...
We present a new finger search tree with O(1) worst-case update time and O(log log d) expected search time with high probability in the Random Access Machine (RAM) model of comput...
Alexis C. Kaporis, Christos Makris, Spyros Sioutas...
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
The observation models in tracking algorithms are critical to both tracking performance and applicable scenarios but are often simplified to focus on fixed level of certain target...
Estimating the pose of an imaging sensor is a central research problem. Many solutions have been proposed for the case of a rigid environment. In contrast, we tackle the case of a...