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In the system (pictured), students had to consider the theoretical requirements of capturing 3D data describing the trajectory of the ball and then put that into practice to evaluate the cameras, lenses, software and lighting needed. The students eventually developed an app called “Kick It, Track It,” that would allow players to score points by trying to hit different targets in the goal.
2013-2014: Gesture recognition project
In 2013-2014, students undertook the task of developing a gesture recognition scheme for environments where a touchscreen is not appropriate (such as theaters, laboratories, mechanic workshops, etc.) This project focused on: pinch (for zoom), swipe (for scroll) and a two-handed ‘select’ gesture. Students tested different cameras to show that speed was more important than resolution, and identified ambient effects (lighting, clothing, background) and ways to minimize them. For software, the team used STEMMER’s CVB’s Manto image recognition and classification tool.
2014-2015: Food packaging inspection project
The current educational vision project involves the design and implementation of a machine vision system that automatically inspects breakfast cereal boxes. The system features a freestanding circular conveyor system with three different cameras at three inspection stations that will be used to carry out print inspection, OCR, and 3D inspection of the box to check size, confirm box closure, and to indicate damage. The students recently finalized camera position and chose the optics, and were able to acquire some test images to allow for the commencement of the system software design and progress the lighting arrangements. Upon completion, the system will be on display at the prestigious Manufacturing Technology Centre, in Anstey, Coventry.
STEMMER hopes that, as a result of these projects, many students will have an interest in engineering and machine vision in the future.
View the STEMMER press release.
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