Online robust dictionary learning

Online dictionary learning is particularly useful for pro-cessing large-scale and dynamic data in computer vision. It, however, faces the major difficulty to incorporate robust functions, rather than the square data fitting term, to han-dle outliers in training data. In this paper, we propose a new online framework enabling the use of 1 sparse data fitting term in robust dictionary learning, notably enhancing the usability and practicality of this important technique. Ex-tensive experiments have been carried out to validate our new framework. 1