In recent years, local pattern based object detection and recognition have attracted increasing interest in computer vision research community. However, to our best knowledge no p...
Yadong Mu, Shuicheng Yan, Yi Liu, Thomas S. Huang,...
Finding latent patterns in high dimensional data is an important research problem with numerous applications. Existing approaches can be summarized into 3 categories: feature selec...
In this paper, we investigate a new approach to process queries in data stream applications. We show that reference locality characteristics of data streams could be exploited in ...
Feifei Li, Ching Chang, George Kollios, Azer Besta...
This work provides a framework for learning sequential attention in real-world visual object recognition, using an architecture of three processing stages. The first stage rejects...
We introduce a new method that characterizes typical local image features (e.g., SIFT [9], phase feature [3]) in terms of their distinctiveness, detectability, and robustness to i...