1. Motion Detection Using MATLAB Laura DeMar Jin Han Advisor: Professor Rudko

2. Project Goals Model an animal’s visual perception of movements in natural scenes  Use an elementary motion detector of the correlation type  Study an animal’s response to an idealized input stimulus Provide a correct model that gives insight into insect’s reaction to prey and food and non-reaction to background motion

3. Introduction Bernhard Hassentein and Werner Reichardt  Did series of behavioral experiments on motion vision in insects  Wasps, bees, and flies Led to development of the correlation-type motion detector, also known as the Reichardt Detector

4. Correlation Model Two mirror subunits Each subunit has a delay and multiplication Image Frames  Object moves by n0 pixels from frame to frame Imprint  Delayed by a time constant D Output  Multiplication of this object with its imprint  Maximum response when D = n0

5. Spatial filter Symmetric Gaussian filter Edge enhancement Spatial Filter mask Spatially filtered object with size L=20. n0 = 1, D = 6, and tau = 1.5

6. Temporal Filter  First-order lowpass filter  Filtered response decays exponentially  Filter gain is inversely proportional to the time constant Spatially and Temporally Filtered Object with length L=6. Time constant is 1.5 and D=3

7. Object Simulation Idealized object  Matrix of ones representing a white rectangle  Size: length L, width K (Pixels)  Moves across the screen in frames  Variable size and direction  Constant velocity

8. Filtered Moving Object Temporally filtered signals mimic those that would appear in lizard’s retinal image. They decay with time constant tau The larger tau, the longer the memory of the filter Temporally filtered object for tau=20 and n0 = 2

9. Results  For small objects, the gain of the temporal filter is inversely proportional to tau.  The maximum response peaks when the velocity is equal to the correlator distance  Calculated the size of the maximum response for various object sizes, speeds, and memory time constants

10. The Effect of the Time Constant For Different Object Sizes  There is a shift in the peak of the maximum response for large object sizes with different tau.  The peak of the maximum response does not occur when the velocity is equal to the correlation distance (D = 6).  Large objects are not tuned for different values of tau.

11. The Effect of Tau on Correlation Distance and Tuning (Large Object)  For small correlation distance (D) and small tau, the response is broader  The tuning of the motion detector depends on tau

12. Future Work Acceleration Swaying motion Relation with physiological results

13. References J.M Zanker, M.V. Srinivasan, M. Egelhaaf. “Speed Tuning in Elementary Motion Detectors Of the Correlation Type”. Biological Cybernetics, 1999. Alexander Borst and Martin Egelhaaf. “Principles of Visual Motion Detection”. TINS, Vol. 12, No 8, 1989. Alexander Borst. “Models of Motion Detection”. Nature neuroscience supplement, Vol. 3, November 2000. Michael P. Eckert and Jochen Zeil. “Towards an Ecology of Motion Vision”. In: Motion Vision - Computational, Neural, and Ecological Constraints (Edited by Johannes M. Zanker and Jochen Zeil) Springer Verlag, Berlin Heidelberg New York, 2001. Johannes M. Zanker. “An Early-Vision Computational Model to Analyze Motion Signal Distributions in Artificial and Natural Stimuli”. Department of Psychology, Royal Holloway University of London, England. 2001

14. Questions?