Article published In: Human Robot Collaborative Intelligence: Theory and applications
Edited by Chenguang Yang, Xiaofeng Liu, Junpei Zhong and Angelo Cangelosi
[Interaction Studies 20:1] 2019
► pp. 25–41
Lifelong learning for tactile emotion recognition
Published online: 15 July 2019
https://doi.org/10.1075/is.18041.wei
https://doi.org/10.1075/is.18041.wei
Abstract
Tactile emotion recognition provides a lot of valuable information in human-computer interaction, and it has
strong application prospects in many aspects such as smart home and medical treatment. So this situation raises a question: How to
quickly and efficiently let the robot perform the correct emotion recognition? In this work, we develop a lifelong learning
algorithm which is based on the efficient dictionary learning technology, to tackle the tactile emotion recognition across
different tasks. To verify the efficiency of the proposed method, we applied it to two data sets for experimentation: Corpus of
Social Touch (CoST) and our dataset(We built it with a 12X12 array sensor). The results show that the proposed lifelong learning
algorithm achieves satisfactory results.
Keywords: tactile interaction, emotion recognition, Lifelong Learning
Article outline
- 1.Introduction
- 2.Lifelong learning architecture for tactile emotion recognition
- 3.ELM-based lifelong learning algorithm
- 4.Experimental results
- 4.1Datasets
- 4.2Results
- 5.Conclusions
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