@inproceedings{ZivkHeij2002,
authors="Z.Zivkovic, F.van der Heijden",
title ="Better Features to Track by Estimating the Tracking Convergence Region",
booktitle="Proceedings of the International Conference on Pattern Recognition",
year=2002,
abstract="Reliably tracking key points and textured patches 
from frame to frame is the basic requirement for many 
bottom-up computer vision algorithms. The problem of 
selecting the features that can be tracked well is 
addressed here. The Lucas-Kanade tracking procedure is 
commonly used. We propose a method to estimate the size of 
the tracking procedure convergence region for each feature. 
The features that have a wider convergence region around 
them should be tracked better by the tracker. The size of 
the convergence region as a new feature goodness measure is 
compared with the widely accepted Shi-Tomasi feature 
selection criteria."
}