Research:

Heteroscedasticity
Robust Analysis
Bootstrap
Retrieval
Miscellaneous

Code

Publications

Theses

Tutorials

Our research was supported by grants from the National Science Foundation, National Institute of Health and the New Jersey Commission on Science and Technology.

The publications are classified by their main topics and are listed in all the categories that apply. A reverse chronological listing of all the available publications is HERE.

Estimation under Heteroscedasticity
In heteroscedastic data a different covariance matrix is associated with each data point, a situation which appears in many vision tasks due to the geometric constraints.

Robust Analysis of Visual Data
Techniques to handle complex data having multimodal empirical distributions or being corrupted by outliers.

Bootstrap as a Tool for Computer Vision
Bootstrap is a resampling method which allows to infer properties related to the sampling distribution of an estimator from the available single input.

Content-based Retrieval
We are addressing only specific applications (like diagnostic pathology) and performance related issues.

Miscellaneous
Everything else: color processing, invariants.