Joint Geometric and Photometric Visual Tracking Based on Lie Group

This paper presents a novel efficient and robust direct visual tracking method under illumination variations. In our approach, non-Euclidean Lie group characteristics of both geometric and photometric transformations are exploited. These transformations form Lie groups and are parameterized by their corresponding Lie algebras. By applying the efficient second-order minimization trick, we derive an efficient second-order optimization technique for jointly solving the geometric and photometric parameters. Our approach has a high convergence rate and low iterations. Moreover, our approach is almost not affected by linear illumination variations. The superiority of our proposed method over the existing direct methods, in terms of efficiency and robustness is demonstrated through experiments on synthetic and real data.