WARF: P170202US01

Imaging Technique for Recognizing Hand Gestures & Other Micromotions in 3-D


Mohit Gupta, Brandon Smith, Pratham Desai, Vishal Agarwal

The Wisconsin Alumni Research Foundation (WARF) is seeking commercial partners interested developing a cost-competitive speckle imaging technique for measuring non-rigid micromotions on smartphones and other devices.
OVERVIEWWith recent advancements in digital imaging, image sensors have become popular for capturing motion in 3-D. However, measuring small scale motion such as fine hand gestures across a user interface remains challenging. Conventional low-cost cameras can detect motions only down to the millimeter or centimeter scale.

Speckle imaging is a technique currently used to measure microscale motions in a variety of settings, including industrial inspection, scientific imaging and user interfaces (e.g., optical mice). To date, speckle imaging has been limited to measuring 2-D motions of single rigid objects and not suitable for tracking motion toward or away from the sensor (i.e., axial motion).
THE INVENTIONUW–Madison researchers have developed a new imaging technique that analyzes speckle patterns to track extremely small 3-D motions on the order of 10-100 microns. This technique enables, for the first time, precise 3-D measurement of multiple moving objects using low-cost, off-the-shelf components.
BUSINESS OPPORTUNITYThe 3-D gesture recognition and gesture control market is expected to grow to $23.55 billion by 2020 and the global 3-D camera market is expected to grow to $10.8 billion by 2021. For 3-D cameras, the largest technological segments are time-of-flight sensing, stereovision and structured light.

Previous successes in this market include the Microsoft Kinect and the Intel RealSense 3-D camera, but these require components that are more expensive than the present technology. By allowing for 3-D motion detection using inexpensive components, this invention could expand the possible applications for 3-D micromotion detection. This invention could also allow for gesture tracking without requiring a full camera system, alleviating some privacy and power concerns.
  • Gesture recognition for devices such as smartphones and wearable sensors
  • Motion analysis of cells, molecules and other microscopic particles
  • Measures 3-D micromotions of more than one object
  • Motion sensitivity is one to two orders of magnitude better than conventional sensors.
  • Uses inexpensive components that can be scaled down
STAGE OF DEVELOPMENTFeasibility has been demonstrated with a hardware prototype consisting of a lens-less sensor and a laser pointer. The researchers have developed a high speed and accurate finger gesture recognition system that can be incorporated into various interactive wearable devices.
For More Information About the Inventors
Contact Information
For current licensing status, please contact Jeanine Burmania at or 608-960-9846.
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