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MOVING OBJECTS SEGMENTATION AND ITS APPLICATIONS

MOVING OBJECTS SEGMENTATION AND ITS APPLICATIONS. Proposed Algorithm. 1. smoothing process 2.moving algorithm 3.template matching scheme 4.background estimation 5.post-processing. Smoothing Processing. 取出 Y, C b , C r. Smoothing Processing. Median filtering to smooth Y.

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MOVING OBJECTS SEGMENTATION AND ITS APPLICATIONS

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  1. MOVING OBJECTS SEGMENTATION AND ITS APPLICATIONS

  2. Proposed Algorithm 1.smoothing process 2.moving algorithm 3.template matching scheme 4.background estimation 5.post-processing

  3. Smoothing Processing 取出 Y, C b, C r

  4. Smoothing Processing Median filtering to smooth Y Result the processed Y’

  5. Smoothing Processing

  6. Moving Object Segmentation Adopt a spatial-temporal approach to segment object X-y-t to x-t image

  7. 3D-2D Y = 179 Row data of x-t means a pixel 180*320 320*240*180

  8. Moving or static pixel

  9. Refinement algorithm M1(x,t), M2(x,t) and M3(x,t) correspond to red, green and blue channels moving (f(x,t)=1) or static (f(x,t)=0)

  10. Refinement algorithm L pixels (L frame length) in a row data

  11. Minimun squared error The problem of Eq.(5) is solved by using the pseudoinverse operation, which is based on minimum squared-error (MSE) method [8]. The solution W is formulated as,

  12. Pseudoinverse M† is called the pseudoinverse of matrix M defined as,

  13. Moving or static pixel 原: 改: Moving piexl static piexl

  14. Threshold calculate the means μ and variances σ22 of state values State value pixel

  15. Gaussian distribution of two states State value Static pixel Moving pixel Probability,p(x|s)

  16. Discriminate function g(x) Threshold = 0.39m Weighting value： [ω1 , ω2 , ω3 ] =[0.0002,-0.0326,0.0315]

  17. X-T marked graph

  18. X-Y marked graph Original x-y marked image

  19. Multiple object detection Start frame End frame

  20. Search template Color different

  21. Search template u,v 搜尋範圍

  22. Search template-min Then refine the marked values b(x,y) of current frame,

  23. Background estimation Based on x-t sliced image If moving pixel a(x,t)=1 If static pixel a(x,t)=0

  24. Post-processing By template =>

  25. Morphology modification

  26. Result

  27. Result

  28. Video edit

  29. Video edit

  30. END

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