Title :
Efficient region tracking with parametric models of geometry and illumination
Author :
Hager, Gregory D. ; Belhumeur, Peter N.
Author_Institution :
Dept. of Comput. Sci., Yale Univ., New Haven, CT, USA
fDate :
10/1/1998 12:00:00 AM
Abstract :
As an object moves through the field of view of a camera, the images of the object may change dramatically. This is not simply due to the translation of the object across the image plane; complications arise due to the fact that the object undergoes changes in pose relative to the viewing camera, in illumination relative to light sources, and may even become partially or fully occluded. We develop an efficient general framework for object tracking, which addresses each of these complications. We first develop a computationally efficient method for handling the geometric distortions produced by changes in pose. We then combine geometry and illumination into an algorithm that tracks large image regions using no more computation than would be required to track with no accommodation for illumination changes. Finally, we augment these methods with techniques from robust statistics and treat occluded regions on the object as statistical outliers. Experimental results are given to demonstrate the effectiveness of our methods
Keywords :
computational geometry; computer vision; image sequences; lighting; motion estimation; optical tracking; statistical analysis; computational geometry; geometric distortions; illumination; image regions; light sources; machine vision; motion estimation; object tracking; parametric models; region tracking; statistical outliers; Cameras; Computational geometry; Light sources; Lighting; Motion estimation; Parametric statistics; Real time systems; Robustness; Target tracking; Video sequences;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on