Empirical Evaluation Methods in Computer Vision

Automated performance evaluation of range image segmentation algorithms training/test data partitioning for empirical performance evaluation analyzing PCA-based face recognition algorithms -eigenvector selection and distance measures design of a visual system for detecting natural events by the use of an independent visual estimate - a human fall detector task-based evaluation of image filtering within a class of geometry-driven-diffusion algorithms a comparative analysis of cross-correlation matching algorithms using a pyramidal resolution approach performance evaluation of medical image processing algorithms.