Dynamic Programming Stereo on Real-World Sequences

Abstract

This paper proposes a way to approximate ground truth for real-world stereo sequences, and applies this for evaluating the performance of di erent variants of dynamic programming stereo analysis. This illustrates a way of performance evaluation, also allowing to derive sequence analysis diagrams. Obtained results di er from those obtained for the discussed algorithms on smaller, or engineered test data. This also shows the value of real-world testing.