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Maximum Response Experimentation

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Presentation on theme: "Maximum Response Experimentation"— Presentation transcript:

1 Maximum Response Experimentation
Senior Project – Electrical Engineering Motion Detection Using MATLAB Laura DeMar, Jin Han Advisor: Prof. Rudko Objectives Model a lizard’s visual perception of movements in natural scenes Use an elementary motion detector of the correlation type In the correlation-type movement detector two mirror subunits have a delay and multiplication. The spatially filtered input is correlated at a given distance with the imprint of the preceding frames given by the temporal filtered output. Maximum Response Experimentation Calculated the size of the maximum response for various object sizes, speeds, and memory time constants. Input Simulation Movie with several frames, in which an object moves with constant velocity n0 from frame to frame. Filtering Results There is a shift in the desired peak of the maximum response for large object sizes with different tau. Thus, the peak of the maximum response does not occur when its velocity is equal to the correlation distance Large objects are not tuned for different memory time constants For a small correlation distance and a small tau, the maximum response is broader Tuning of the motion detector depends on tau because there were more maximum response peaks for a small tau Gain is inversely proportional to the time constant Program can be tested further for varying speeds between frames Results need to be correlated with lizard physiological data Temporal Filter Lowpass filter Time constant tau determines memory of the filter The larger tau, the longer the memory of the filter Filtered signals mimic those that would appear in lizard’s retinal image Spatial Filter Symmetric Gaussian filter Enhances the edges of the object


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