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— Presentation at ACM ISS 2016 —
November 25, 2016
ACM Interactive Surfaces and Spaces (ISS) 2016 was held in Niagara Falls, Canada on November 6 to 9, 2016. As the 11th event in an annual series starting in 2006, ACM ISS is the premier venue for research addressing the design, development and use of new and emerging tabletop, digital surface, interactive spaces and multi-surface technologies. In ISS'16, there were 33 oral presentations, 23 poster presentations, and 16 demo presentations. I had a poster presentation titled "Touch Detection Technique for Various Surfaces Using Shadow of Finger".
Fig. 1 Poster for presentation
Recently, Tablet PCs and smartphones are used throughout the world, and touch interactions are commonly used for such devices. Some display devices such as see-through head-mounted displays (HMDs) or projectors have also been developed that enables us to visualize information on various surrounding surfaces. Since touch interactions have become a natural operation method, a system in which users can manipulate information on surrounding surfaces with touch interactions will be required.
To develop such a system, touch detection on various surfaces is an important underlying technology. Various surfaces means surrounding surfaces such as walls, desks, and screens. Additionally, these surfaces are not always flat but curved or have protruding objects. Although there have been some studies on enabling touch interaction on surrounding surfaces, these studies have some constraints, such as a surface must be flat or the operation area is narrow.
Fig. 2 The shapes of a finger's shadows vary
depending on the distance between the surface
Therefore, we propose new touch detection technique which utilizes the shadows of a finger, and developed a prototype system with an infrared (IR) camera and two IR lights. As shown in Figure 2, since the shapes of a finger's shadows vary drastically depending on the distance between the surface and finger, our prototype system can detect a touch. Additionally, a touch on a curved surface or surface with protruding objects can be detected because we can observe shadows even on these surfaces.
In order to improve the accuracy of the estimated touch position, we also introduce multiple regression analysis (MRA) into the estimation algorithm of the touch position. The results of the experiment on the accuracy of estimated touch position show that estimating touch position based on MRA significantly improves the accuracy and target accuracy of touch position.
Future work will include improvement in touch detection accuracy, evaluation on various surfaces, and considerations necessary for practical use of the system.
(By NIIKURA Takehiro)