Title
SpecTrans: Versatile Material Classification for Interaction with Textureless, Specular and Transparent Surfaces
Abstract
Surface and object recognition is of significant importance in ubiquitous and wearable computing. While various techniques exist to infer context from material properties and appearance, they are typically neither designed for real-time applications nor for optically complex surfaces that may be specular, textureless, and even transparent. These materials are, however, becoming increasingly relevant in HCI for transparent displays, interactive surfaces, and ubiquitous computing. We present SpecTrans, a new sensing technology for surface classification of exotic materials, such as glass, transparent plastic, and metal. The proposed technique extracts optical features by employing laser and multi-directional, multi-spectral LED illumination that leverages the material's optical properties. The sensor hardware is small in size, and the proposed classification method requires significantly lower computational cost than conventional image-based methods, which use texture features or reflectance analysis, thereby providing real-time performance for ubiquitous computing. Our evaluation of the sensing technique for nine different transparent materials, including air, shows a promising recognition rate of 99.0%. We demonstrate a variety of possible applications using SpecTrans' capabilities.
Year
DOI
Venue
2015
10.1145/2702123.2702169
CHI
Keywords
Field
DocType
material classification,user interfaces,context-aware mobile computing,multi-spectral sensing,ubiquitous computing,laser speckle,sensors
Computer vision,Material classification,Speckle pattern,Wearable computer,Computer science,Specular reflection,Artificial intelligence,Ubiquitous computing,Reflectivity,Material properties,Cognitive neuroscience of visual object recognition
Conference
Citations 
PageRank 
References 
7
0.50
32
Authors
8
Name
Order
Citations
PageRank
Munehiko Sato124720.15
Shigeo Yoshida282.21
Alex Olwal382857.27
Boxin Shi438145.76
Atsushi Hiyama513129.01
Tanikawa, T.660695.07
M Hirose71341224.70
Ramesh Raskar85305422.69