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Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons84037

Lampert,  CH
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Dept. Empirical Inference, Max Planck Institute for Intelligent System, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84135

Peters,  J
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Citation

Lampert, C., & Peters, J. (2012). Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components. Journal of Real-Time Image Processing, 7(1), 31-41. doi:10.1007/s11554-010-0168-3.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-B802-4
Abstract
We describe RTblob, a high speed vision system that detects objects in cluttered scenes based on their color and shape at a speed of over 800 frames/s. Because the system is available as open-source software and relies only on off-the-shelf PC hardware components, it can provide the basis for multiple application scenarios. As an illustrative example, we show how RTblob can be used in a robotic table tennis scenario to estimate ball trajectories through 3D space simultaneously from four cameras images at a speed of 200 Hz.