4 February 2013 Finger tracking for hand-held device interface using profile-matching stereo vision
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Proceedings Volume 8662, Intelligent Robots and Computer Vision XXX: Algorithms and Techniques; 86620H (2013); doi: 10.1117/12.2013702
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States
Abstract
Hundreds of millions of people use hand-held devices frequently and control them by touching the screen with their fingers. If this method of operation is being used by people who are driving, the probability of deaths and accidents occurring substantially increases. With a non-contact control interface, people do not need to touch the screen. As a result, people will not need to pay as much attention to their phones and thus drive more safely than they would otherwise. This interface can be achieved with real-time stereovision. A novel Intensity Profile Shape-Matching Algorithm is able to obtain 3-D information from a pair of stereo images in real time. While this algorithm does have a trade-off between accuracy and processing speed, the result of this algorithm proves the accuracy is sufficient for the practical use of recognizing human poses and finger movement tracking. By choosing an interval of disparity, an object at a certain distance range can be segmented. In other words, we detect the object by its distance to the cameras. The advantage of this profile shape-matching algorithm is that detection of correspondences relies on the shape of profile and not on intensity values, which are subjected to lighting variations. Based on the resulting 3-D information, the movement of fingers in space from a specific distance can be determined. Finger location and movement can then be analyzed for non-contact control of hand-held devices.
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Yung-Ping Chang, Dah-Jye Lee, Jason Moore, Alok Desai, Beau Tippetts, "Finger tracking for hand-held device interface using profile-matching stereo vision", Proc. SPIE 8662, Intelligent Robots and Computer Vision XXX: Algorithms and Techniques, 86620H (4 February 2013); doi: 10.1117/12.2013702; http://dx.doi.org/10.1117/12.2013702
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KEYWORDS
Detection and tracking algorithms

Control systems

Image segmentation

Signal processing

Stereo vision systems

3D image processing

Algorithm development

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