Spatiograms versus Histograms for Region-Based Tracking

We introduce the concept of a spatiogram, which is a generalization of a histogram that includes potentially higher order moments. A histogram is a zeroth-order spatiogram, while second-order spatiograms contain spatial means and covariances for each histogram bin. This spatial information still allows quite general transformations, as in a histogram, but captures a richer description of the target to increase robustness in tracking. We show how to use spatiograms in kernel-based trackers, deriving a mean shift procedure in which individual pixels vote not only for the amount of shift but also for its direction. Experiments show improved tracking results compared with histograms, using both mean shift and exhaustive local search. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) San Diego, California, June 2005 c 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for c...

• Type: Conference
• Year: 2005
• Where: CVPR
• Authors: Stan Birchfield, Sriram Rangarajan
• Keywords: Computer Vision, CVPR 2005, Exhaustive Local Search, Histogram Bin, IEEE Conference, Mean Shift Procedure, Spatial Means