Lack of robustness against noise uncertainty is a bottleneck of current spectrum sensing strategies to detect the primary signals. Due to noise uncertainty, the performance of tra...
Graph-based methods form a main category of semisupervised
learning, offering flexibility and easy implementation
in many applications. However, the performance of
these methods...
Wei Liu (Columbia University), Shih-fu Chang (Colu...
In this paper we propose a robust visual tracking method
by casting tracking as a sparse approximation problem in a
particle filter framework. In this framework, occlusion, corru...
We present a robust elastic and partial matching metric
for face recognition. To handle challenges such as pose, facial
expression and partial occlusion, we enable both elastic
...
We propose a novel efficient algorithm for robust tracking of a fixed number of targets in real-time with low failure rate. The method is an instance of Sequential Importance Resa...