Left to Right: Vy Tran, Paul Morris, Michael Keller, Pablo Adell, Mary Pengelley
Meeting Times: Fridays at 4:15 PM
Room: Behavioral Sciences 405, Florida Atlantic University
Michael Keller -Undergraduate Researcher, Team Leader of GPA Team
Paul Morris– Graduate Researcher, Masters of Computer Science Candidate
Vy Tran– Undergraduate Researcher
Pablo Adell- Undergraduate Researcher, Spanish Exchange Student
Mary Pengelley, RPT, DPT, ATP–Director of Physical Therapy at Progressive Pediatric Therapy, Special Professional Advisor to 3D Camera Team
The 3D Kinect Camera is a revolutionary device used for body tracking, gaming, and other applications. This team’s current goal is to use the camera to track the body’s movements and discourage bad habits. For example, say someone is watching a movie and they start to slouch over. Our goal is to make an application, known as the Good Posture Application (GPA) to interface the Kinect with the volume control of the device the user is working with and lower the volume, so as to encourage them to sit up straight. So far, the GPA is currently able to track several people at a time; detect their faces, and display the data on screen. We are working on facial recognition as our next long term feature. This will enable us to save the posture data of the users so they can see their progress over time. We will also add sound feedback very soon as a good first step towards linking into the system’s volume control. With these changes implemented, we hope to release the GPA for wide use. This project is very useful for those who want to eliminate subconscious physical habits that may be detrimental to their health.
Below you will find screenshots of a working prototype of the GPA. As you can see, it is returning a small green number for good posture and a large red number for bad posture. The closer the number is to 0 and the greener the number, the better the person’s posture is and vice versa for larger red numbers.
October 2017- Below you will find a promo of our latest version of the GPA. Observe that it now rates participants using a letter grade in addition to the coloration of the number that denotes the math behind the scenes. Observe also that it now can track up to 6 people at once, by the color of their skeleton, and that the program can also perform face detection. Our next goal is to implement facial recognition, so that the program is able to distinguish between specific people, not just colors.
November 2017- Below you will find the latest stable version of the GPA with the ability to track up to 6 people at once by skeleton color as well as to track people without lighting.
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