A University of Granada research team has evaluated the accuracy of several models that estimate movement, and combined the responses of four movement detection cells, two of which are static, either on or off, and two are transitory, which have varying degrees. The objective was to create an artificial retina by combining movement and attention data based on information provided by a visual system capable of selectively capturing moving objects in real time. An event-driven model, which allows the system to focus only on areas of activity, was critical to the process in both the movement processing model and in the multimodal selective attention model.
One result of the study is the ability to estimate movement reasonably accurately using the responses from the four cells. "By selecting only 10 to 20 percent of the information, which we selected on the basis of reliability of the measurements, we obtained precise results at a lower computational cost and with greater stability," says Granada researcher Fran Barranco.
The researchers also developed advanced integrated intelligent sensors that can pre-process a scene using techniques similar to those used by retinas. The devices created by the project are designed for use in video surveillance and monitoring applications, though their low power consumption also makes them well suited for implants in patients or in research dedicated to understanding the brain, particularly the visual system.
From Plataforma SINC
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