Publication | Closed Access
Retinal ganglion cell software and FPGA model implementation for object detection and tracking
11
Citations
5
References
2016
Year
Event CameraEngineeringDynamic Vision SensorFpga Model ImplementationGanglion CellImage AnalysisRetinaVision SensorMachine VisionOphthalmologyObject DetectionComputer EngineeringMoving Object TrackingComputer ScienceSpartan6 FpgaObject PositionComputer VisionMotion DetectionCellular Neural NetworkEye TrackingMedicineMotion Analysis
This paper describes the software and FPGA implementation of a Retinal Ganglion Cell model which detects moving objects. It is shown how this processing, in conjunction with a Dynamic Vision Sensor as its input, can be used to extrapolate information about object position. Software-wise, a system based on an array of these of RGCs has been developed in order to obtain up to two trackers. These can track objects in a scene, from a still observer, and get inhibited when saccadic camera motion happens. The entire processing takes on average 1000 ns/event. A simplified version of this mechanism, with a mean latency of 330 ns/event, at 50 MHz, has also been implemented in a Spartan6 FPGA.
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