Leclerc, Y. G. and Luong, Q. T. and Fua, P. Self-Consistency, A Novel Approach to Characterizing the Accuracy and Reliability of Point-Correspondence Algorithms, in One-day Workshop on Performance Characterisation and Benchmarking of Vision Systems, Las Palmas de Gran Canaria, Canary Islands Spain, 1999.
Abstract
We present a framework for reliably and robustly detecting changes in terrain (or other 3-D objects) over time. We first present our
framework, which consists of a method for modeling terrain using a novel image-matching measure called the coding loss, a method for estimating the accuracy of the resulting terrain models called self-consistency, and method for detecting changes based on this estimate. We then present experiments using our framework.