January 2008
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January 2008. Fast Multi Class Distance Transforms for Video Surveillance. Theo Schouten Egon van den Broek. Distance Transformation. distance map D(p) = min { dist(p,q), q  O }. Multi Class DT. class map C(p) = C(q), q  O, dist(p,q) == D(p).

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January 2008

January 2008

Fast Multi Class Distance Transforms for Video Surveillance

Theo Schouten

Egon van den Broek


Distance transformation
Distance Transformation

  • distance map D(p) = min { dist(p,q), q  O }


Multi class dt
Multi Class DT

  • class map C(p) = C(q), q  O, dist(p,q) == D(p)


Used original distance transformation
Used original distance transformation

  • CH11: city-block DT of Rosenfeld and Pfaltz

  • CH34: chamfer 3,4 of Borgefors

  • EDT4: 4-scan semi-exact EDT of Shih and Liu

  • EDT2: 2-scan semi-exact EDT of Shih and Wu

  • EDLT: EDT method of Maurer, Qi and Raghavan

    • based on dimension reduction

    • proces first rows then columns

    • partial Voronoi diagram for each row, column

  • FEED: or own EDT


Fast exact euclidean distance feed
Fast Exact Euclidean Distance (FEED)

border pixels bisection lines precalculate ED

  • each q  O

    feeds its ED to all p:D(p) = min ( D(p), ED(q,p))

  • Faster than EDLT, EDT4, EDT2

  • More implementation effort

    • more lines of code

    • parameters and strategies


Multi class extension
Multi class extension

  • scan methods (CH11, CH34, EDT4, EDT2):

    • compare d(p) with d’s of neighbours

    • add compare c(p) with c’s of neighbours

  • EDLT:

    • add extra vector to contain class of Voronoi points

    • used to set class of filled-in points on row, column

  • FEED:

    • change update step D(p) = min ( D(p), ED(q,p))

    • if( ED(q,p) < D(p) ) D(p) = ED(q,p), C(p)=C(q)



Video frames
Video frames

D fixed+mov (p) = if( D fixed (p) < D mov (p) )

then Dfixed+mov(p) = Dfixed(p) , Cfixed+mov(p) = Cfixed(p)

else Dfixed+mov(p) = Dmov(p) , Cfixed+mov(p) = Cmov(p)


Fast moving part calculation
Fast moving part calculation

  • fast location moving object

    • sequence of refining scans over the image

    • using RLE encoding of fixed objects

  • use dmax = max ( Dfixed(p) ) to calculate D (C ) mov

    • only over part of the frame

    • bounding box of moving object extended by dmax

  • combining fixed and moving D (C ) only for part

  • same memory locations for D fixed and D fixed+mov


Extra speed up for feed
Extra speed-up for FEED

  • merge the application of FEED on the moving object

    • with combining fixed and moving D (C ):

    • replace initialization D(p)= if( p  O ) 0 else 

    • by D(p) = D fixed (p)

  • not possible for other methods

    • only partial evaluations of D during scans

  • further the RLE encoding is used to speed-up FEED





Conclusion
Conclusion

  • extended several DT’s to

    • handle images with multi class objects

    • and to faster processing of video frames

      • with fixed and one moving multi class objects

  • extension methods applicable to all scans based DT’s

  • our Fast Exact Euclidean Distance transformation

    • is faster (6-10) than other MC (semi-)exact EDT’s

    • on video frames even faster than city-block

  • more implementation effort

    • tune to cache-systems, image characteristics


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