Regression analysis (fitting a model to noisy data) is a basic technique in computer vision,
Robust regression methods that remain reliable in the presence of various types of noise are …

This correspondence presents a segmentation and fitting method using a new robust
estimation technique. We present a robust estimation method with high breakdown point …

The least-squares method is the most commonly used technique for fitting an ellipse through
a set of points. However, it has a low breakdown point, which means that it performs poorly …

Vision systems play an important role in many intelligent transportation systems (ITS)
applications, such as traffic monitoring, traffic law reinforcement, driver assistance, and …

Standard techniques for ellipse fitting such as the least squares method and the Hough
Transform either make certain assumptions about the type of noise distribution, or require …

The discretization of the Hough transform parameter plane is considered. It is shown that the
popular accumulator method implies sampling of a nonbandlimited signal. The resultant …

Matching two sets of lines is a basic tool that has applications in many computer vision
problems such as scene registration, object recognition, motion estimation, and others. Line …

The problem of fitting a straight line to a planar set of points is reconsidered. A parameter
space computational approach capable of fitting one or more lines to a set of points is …

This study compares the ability of different robust regression estimators to detect and classify
outliers. Well-known estimators with high breakdown points were compared using simulated …

With the advent of multiprocessors on the desktop, software applications are increasingly
likely to adopt multithreaded architectures. To cope with the complexity of concurrent …