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Active Visual-Tactile Cross-Modal Matching
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DOI：10.1109/TCDS.2018.2819826.png)
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Abstract
En 中文
Tactile and visual modalities frequently occur in cognitive robotics. Their matching problem is of highly interesting in many practical scenarios since it provides different properties about objects. In this paper, we investigate the active visual-tactile cross-modal matching problem which is formulated as retrieving the relevant sample in unlabeled gallery visual dataset in response to the tactile query sample. Such a problem exhibits a nontrivial challenge that there does not exist sample-to-sample pairing relation between tactile and visual modalities. To this end, we design a shared dictionary learning model which can simultaneously learn the projection subspace and the latent shared dictionary for the visual and tactile measurements. In addition, an optimization algorithm is developed to effectively solve the shared dictionary learning problem. Based on the obtained solution, the visual-tactile cross-modal matching algorithm can be easily developed. Finally, we perform experimental validations on the PHAC-2 datasets to show the effectiveness of the proposed visual-tactile cross-modal matching framework and method.
Keywords:
Cross-modal matching
dictionary learning
tactile modality
visual modality
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