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Foil 69 Track Finding when there are a lot of tracks

From Physical Optimization and Physical Computation CPSP713 Case studies in Computational Science -- Spring Semester 1996. by Geoffrey C. Fox
1 Case II: Very Many Tracks
  • In one space (plus time) this tracking problem is formally equivalent to edge detection in vision.
  • In vision, measurements are the discontinuities (differentiations) of color / motion / texture etc. in an image. Edge detection involves linking this basic data into "lines" which will separate regions of image.
    • Solve by neural network method
    • h(x) = 1 if there is an edge
    • = 0 if there is no edge
    • In vision x = (x,y), tracking x = (x,t)
  • h is a field theory formalism, whereas Kalman Filter is a particle formalism
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