Low-Cost Multi-Touch Sensing through Frustrated Total Internal Reflection

Overview

This paper discusses frustrated total internal reflection as a simple, inexpensive, and scalable technique for enabling high-resolution multi-touch sensing on rear-projected interactive surfaces. In more detail, they go over previous applications, provide implementation details, discuss results from their initial prototype, and outline future directions.

Previous Applications

This technique was used in application such as finger prints since at least the 1960’s, a painting application in the 1970’s, robotics, and other applications. This technique is widely known and has been around for a long time. The principle is also used for fiber optics. This is a pro since the technology is familiar and has been studied and implemented already. This brings down the cost for using this technique.

Implementation Details

Simple imaging techniques such as rectification, background subtraction, noise removal, and connected component analysis are used for each frame of data. Since these algorithms are widely known and used, this is a pro when it comes to implementing this technology. Since this technique is camera-based, this implies that there will be a drawback with various backgrounds and background lighting. This is a con for this technique compared to a capacitor based system that is not affected by background noise.

Results from Initial Prototype

There was a disparity from using a ¼” waveguide for their prototype, but they said there was no reason, other than ease of implementation, to use a smaller one. Their surface became contaminated easily after usage which caused problems. However, with the adaptable background algorithm, it will learn the noise and not consider it as a touch. Also, the system depends on the optical qualities of the object being sensed and this will cause the system to not detect non-human touch objects such as a mug or hand with glove. Also, a user with dry skin will have to push harder on the screen to achieve the success of a user without dry skin. The surface will have to be cleaned periodically to maintain accuracy. Also noted, is that some of these issues could be remedied by engineering a compliant surface overlay.

Future Directions

They discuss upgrading the system to differentiate between different points of contact. Currently, there is no way to distinguish if two finger came from the same hand.

Discussion

• Low-level algorithms to detect touch, light, background, etc...
• How does this technique compare to 3M & MS Surface systems?
• Adaptive algorithms to target user attributes: dry skin vs. non-dry skin