While stroking a rigid tool over an object surface, vibrations induced on the tool, which represent the interaction between the tool and the surface texture, can be measured by means of an accelerometer. Such acceleration signals can be used to recognize or to classify object surface textures. The temporal and spectral properties of the acquired signals, however, heavily depend on different parameters like the applied force on the surface or the lateral velocity during the exploration. Robust features that are invariant against such scan-time parameters are currently lacking, but would enable texture classification and recognition using uncontrolled human exploratory movements. We introduce a haptic texture database which allows for a systematic analysis of feature candidates. The database includes recorded accelerations measured during controlled and well-defined texture scans, as well as uncontrolled human free hand texture explorations for 69 different textures.
LMT Haptic Texture Database
Matti Strese, Jun-Yong Lee, Clemens Schuwerk, Qingfu Han, Hyoung-Gook Kim and Eckehard Steinbach A Haptic Texture Database for Tool-mediated Texture Recognition and Classification Submitted to the IEEE Int. Symposium on Haptic Audio-Visual Environments and Games (HAVE), Dallas, USA, Oktober 2014.