09:55 - 11:10 | Tue 30 May | Room 4711/4712 | TUA7
In this paper, we exploit the intrinsic relation between different adjective labels and develop a novel multi-label dictionary learning and sparse coding method which is improved by introducing the structured output association information. Such a method makes use of the label correlation information and is more suitable for the multi-label tactile understanding task. In addition, we develop a globally-convergent iterative algorithms to solve the dictionary learning problem. Finally, we perform extensive experimental validations on the public available tactile sequence dataset PHAC-2 and show the advantages of the proposed method.
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