Transcript Titel van de presentatie

January 2008
Fast Multi Class Distance Transforms
for Video Surveillance
Theo Schouten
Egon van den Broek
Fast Multi Class DT for Video
Distance Transformation
•distance map
D(p) = min { dist(p,q), q  O }
Fast Multi Class DT for Video
Multi Class DT
•class map
C(p) = C(q), q  O, dist(p,q) == D(p)
Fast Multi Class DT for Video
Used original distance transformation
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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 Multi Class DT for Video
Fast Exact Euclidean Distance (FEED)
• each q  O
border pixels
bisection lines
feeds its ED to all p:
precalculate ED
D(p) = min ( D(p), ED(q,p))
•Faster than EDLT, EDT4, EDT2
•More implementation effort
•more lines of code
•parameters and strategies
Fast Multi Class DT for Video
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)
Fast Multi Class DT for Video
Timing Multi Class DT
time in P-4 3 GHz 1024 MB
s/pixel 12 KuOps, 16KB; 2048 KB
P-M 1.6 GHZ 512 MB
32 KB, 32 KB ; 2048 KB
image
size
640 x
480
1280 x
960
2560 x
1920
640 x
480
1280 x
960
2560 x
1920
FEED
0.033
0.037
0.045
0.036
0.048
0.119
EDLT
0.066
0.076
0.195
0.101
0.116
0.317
EDT2
0.059
0.060
0.066
0.100
0.104
0.111
CH11
0.013
0.013
0.014
0.018
0.023
0.025
Fast Multi Class DT for Video
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 Multi Class DT for Video
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
Fast Multi Class DT for Video
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
Fast Multi Class DT for Video
Timing video Multi Class DT
time in
s/pixel
P-4 3 GHz 1024 MB
12 KuOps, 16KB; 2048 KB
P-M 1.6 GHZ 512 MB
32 KB, 32 KB ; 2048 KB
640 x 480 full
7 fixed
fixed
video
full
fixed
video
FEED
0.035
0.039
0.003
0.041
0.045
0.004
EDLT
0.066
0.070
0.025
0.102
0.105
0.037
EDT2
0.060
0.064
0.026
0.102
0.106
0.040
CH11
0.012
0.017
0.013
0.018
0.023
0.019
Fast Multi Class DT for Video
Timing video MCDT
time in
s/pixel
P-4 3 GHz 1024 MB
12 KuOps, 16KB; 2048 KB
P-M 1.6 GHZ 512 MB
32 KB, 32 KB ; 2048 KB
640 x 480
13 fixed
full
fixed
video
full
fixed
video
FEED
0.033
0.037
0.002
0.038
0.043
0.002
EDLT
0.058
0.062
0.012
0.091
0.095
0.019
EDT2
0.061
0.066
0.013
0.104
0.109
0.020
CH11
0.012
0.017
0.007
0.018
0.023
0.009
Fast Multi Class DT for Video
Examples
Fast Multi Class DT for Video
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