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Senior Project: Motion Detection. Jin Han Laura DeMar Advisor: Professor Rudko. Background. Reichardt Model Originated from study of computer vision and later applied to biological motion Mathematically obtains exact measurement of local velocity dx/dt. Movement Detector.
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Senior Project:Motion Detection Jin Han Laura DeMar Advisor: Professor Rudko
Background • Reichardt Model • Originated from study of computer vision and later applied to biological motion • Mathematically obtains exact measurement of local velocity dx/dt
Movement Detector • Correlation type -two mirror subunits -each subunits has a delay and multiplication stage
Movement Detector When delay is the same as the time it takes for the object to move to its next position, there is an output.
Current work • Simulation Methods Dots or bars flash sequentially at different position and with different time interval • Generate a movie with a an impulse, then with a block of ones (rectangle) moving across the screen in frames per second.
Elements:Spatial Filtering • Use two 2D gaussians for two amounts of spatial spreading for a 2D bandpass spatial filter. • Outlines components that have change, thus getting edges in the image. • Takes away high frequency noise and DC components
Elements:Temporal Filtering • Low Pass temporal Filtering – Memory of vision system • One-dimensional filtering using a difference equation • filters pixels from image in time domain.
Future Work • Implement correlator • study sensitivity and range of detected velocities. • Apply correlator to movies recorded in the Lizards’ habitat.