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Senior Project: Motion Detection

Dive into the realm of motion detection with the Reichardt Model, originating from computer vision and biological motion studies, to obtain precise velocity measurements. Current work involves simulating movement detection using spatial and temporal filtering techniques. Future plans include implementing a correlator and analyzing detected velocities in lizards' habitats.

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Senior Project: Motion Detection

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  1. Senior Project:Motion Detection Jin Han Laura DeMar Advisor: Professor Rudko

  2. Background • Reichardt Model • Originated from study of computer vision and later applied to biological motion • Mathematically obtains exact measurement of local velocity dx/dt

  3. Movement Detector • Correlation type -two mirror subunits -each subunits has a delay and multiplication stage

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. Future Work • Implement correlator • study sensitivity and range of detected velocities. • Apply correlator to movies recorded in the Lizards’ habitat.

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