Abstract
Since many properties perceived by the tactile sensors can be characterized by adjectives, it is reasonable to develop a set of tactile adjectives for the tactile understanding. This formulates the tactile understanding as a multilabel classification problem. This chapter exploits the intrinsic relation between different adjective labels and develops a novel dictionary learning 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 multilabel tactile understanding task. In addition, two iterative algorithms are developed to solve the dictionary learning and classifier design problems, respectively. Finally, extensive experimental validations are performed on the publicly available tactile sequence dataset PHAC-2 and show the advantages of the proposed method.
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Liu, H., Sun, F. (2018). Tactile Adjective Understanding Using Structured Output-Associated Dictionary Learning. In: Robotic Tactile Perception and Understanding. Springer, Singapore. https://doi.org/10.1007/978-981-10-6171-4_5
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DOI: https://doi.org/10.1007/978-981-10-6171-4_5
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