Rank-1 L1-norm-based TUCKER2 (L1-TUCKER2) decomposition of 3-way tensors was recently solved exactly, for the first time, by Markopoulos et al.<sup>1</sup> The exact solution to general-rank L1-TUCKER2 remains to date unknown. In this work, we present a novel approximate algorithm for general-rank L1-TUCKER2 decomposition of 3-way tensors. Our algorithm is accompanied by formal convergence and complexity analysis. Our numerical studies illustrate the sturdy corruption resistance of the proposed algorithm compared to state-of-the-art TUCKER2-decomposition counterparts such as GLRAM, HOSVD, and HOOI.
We present a novel method for robust tracking in video frame sequences via L1-Grassmann manifolds. The proposed method represents adaptively the target as a point on the Grassmann manifold, calculated by means of L1-norm Principal-Component Analysis (L1-PCA). For this purpose, an efficient algorithm for adaptive L1-PCA is presented. Our experimental studies illustrate that the presented tracking method, leveraging the outlier resistance of L1-PCA, demonstrates robustness against target occlusions and illumination variations.