Active contours for tracking distributions.
A new approach to tracking using active contours is presented. The class of objects to be tracked is assumed to be characterized by a probability distribution over some variable, such as intensity, color, or texture. The goal of the algorithm is to find the region within the current image, such that the sample distribution of the interior of the region most closely matches the model distribution. Two separate criteria for matching distributions are examined, and the curve evolution equations are derived in each case. The flows are shown to perform well in experiments.
Freedman
Daniel
D
Computer Science Department, Rensselaer Polytechnic Institute, Troy, NY 12180-3590, USA. freedman@cs.rpi.edu
Zhang
Tao
T
D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D015233:Models, Statistical; D009068:Movement / Q000502:physiology*; D010363:Pattern Recognition, Automated; D010783:Photometry / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013382:Subtraction Technique; D014741:Video Recording / Q000379:methods*