Haptic Material Analysis and Classification Inspired by Human Exploratory Procedures
| Autor: | Eckehard Steinbach, Jonas Kirsch, Matti Strese, Lara Brudermueller |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Surface (mathematics)
Adult 0209 industrial biotechnology Computer science 02 engineering and technology Set (abstract data type) User-Computer Interface 020901 industrial engineering & automation Deep Learning Taxonomy (general) 0202 electrical engineering electronic engineering information engineering Feature (machine learning) Humans Artificial neural network business.industry Pattern recognition Robotics Object (computer science) Computer Science Applications Random forest Human-Computer Interaction Touch Perception Exploratory Behavior 020201 artificial intelligence & image processing Artificial intelligence business Parametrization Psychomotor Performance |
| Zdroj: | IEEE transactions on haptics. 13(2) |
| ISSN: | 2329-4051 |
| Popis: | We present a framework for the acquisition and parametrization of object material properties. The introduced acquisition device, denoted as Texplorer2, is able to extract surface material properties while a human operator is performing exploratory procedures. Using the Texplorer2, we scanned 184 material classes which we labeled according to biological, chemical, and geological naming conventions. Based on these real material recordings, we introduce a novel set of mathematical features which align with corresponding material properties defined in perceptual studies from related work and classify the materials using common machine learning techniques. Validation results of the proposed multi-modal features lead to an overall classification accuracy of 90.2% $\pm$ 1.2% and an F $_\text{\text{1}}$ score of 0.90 $\pm$ 0.01 using the random forest classifier. For the sake of comparison, a deep neural network is trained and tested on images of the material surfaces; it outperforms (90.7% $\pm$ 1.0%) the hand-crafted feature-based approach yet leads to more critical misclassifications in terms of the proposed taxonomy. |
| Databáze: | OpenAIRE |
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