This paper introduces a multilinear principal component analysis (MPCA) framework for tensor object feature extraction. Objects of interest in many computer vision and pattern rec...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...
In this paper, we address the problem of robustly recovering several instances of a curve model from a single noisy data set with outliers. Using M-estimators revisited in a Lagran...
Jean-Philippe Tarel, Pierre Charbonnier, Sio-Song ...
The Errors-in-Variables (EIV) model from statistics is often employed in computer vision thoughonlyrarely under this name. In an EIV model all the measurements are corrupted by no...
This paper presents a new stereo matching algorithm based on inter-regional cooperative optimization. The proposed algorithm uses regions as matching primitives and defines the co...
Sparse representation in compressive sensing is gaining increasing attention due to its success in various applications. As we demonstrate in this paper, however, image sparse rep...