An improved maximum likelihood estimator for ellipse fitting based on the heteroscedastic errors-in-variables (HEIV) regression algorithm is proposed. The technique significantly ...
Search by Object Model -- finding an object inside a target image -- is a desirable and yet difficult mechanism for querying multimedia data. An added difficulty is that objects c...
In recent work the authors proposed a wide-ranging method for estimating parameters that constrain image feature locations and satisfy a constraint not involving image data. The p...
Anton van den Hengel, Michael J. Brooks, Wojciech ...
Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
We present an algorithm to estimate the parameters of a linear model in the presence of heteroscedastic noise, i.e., each data point having a different covariance matrix. The algor...