reducing false alarm occurrences in vehicle detection systems · 2011-10-29 · 2 + ) / 2!: , : ) 2...
TRANSCRIPT
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%,:#*'&;E]!
F. Calculate the total number of angular sections, J:
J = 360 / Angle_Per_Zone!
Z. Calculate the total number of radial sections, K:
K = Zone_Map_Diameter / Length_Per_Zone!
c. Calculate the total number of zones, n:
n = J * K!
H. Create a an empty 2D lookup table, Z, with dimensions J x K!
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F. For each vehicle instance in the training set, V:!
F.F. Calculate the center of the bounding box (Cx, Cy):
Cx = (2*Vx + VWidth) / 2
Cy = (2*Vy + VHeight) / 2!
F.Z. Calculate the Angle, A, between point C and the reference
point, R:
A = Atan2(Cy-Ry, Cx-Rx) * (180/PI)!
F.c. Calculate the length, L, between point C and the reference
point, R:
L = Sqrt((Cy-Ry)2 + (Cx-Rx)2)!
Z. Find the zone element, ZA,L given angle A, and length, L!
c. Increment the frequency field for element ZA,L!
H. Repeat Step 1 to Step 3 for all vehicle instances in the
training set!
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F. For a given candidate object W, calculate the angle A, and
length L, with respect to the center of the Zone Map, R:
A = Atan2(Wy-Ry, Wx-Rx) * (180/PI),
L = Sqrt((Wy-Ry)2 + (Wx-Rx)2)!
Z. Find the zone element, ZA,L given angle A, and length, L!
c. For the zone element ZA,L , lookup the location probability pl:!
c.F. If pl > the location probability threshold, pTHRESHOLD , go to
Step 4!
c.Z. Otherwise, go to Step 6!
H. For the zone element ZA,L ,lookup the size information S:!
H.F. Calculate the area of candidate object W:
WAREA = WWIDTH*WHEIGHT!
H.Z. Calculate Size limits SUPPER and SLOWER based on the size
threshold t and the average size SAVERAGE:
SUPPER = SAVERAGE + (2t + t2) * SAVERAGE
SLOWER = SAVERAGE - (2t + t2) * SAVERAGE,
Where 0 < t < 1!
H.c. If the area of candidate object w falls within a the
threshold size limits, that is
if SLOWER < WAREA < SUPPER,
go to Step 5!
H.H. Otherwise go to Step 6!
J. Candidate object w is a vehicle. Keep candidate object w!
/. Candidate object w is not vehicle. Discard candidate object w!
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Implementation
• The radius gap was 30 pixels, and the angle gap was 20 degrees
• Radius ranges from 1 to 240 px
• Angle ranges from 0 to 359 degrees
• This creates a total of 144 zones
• The weights were implemented as:w1 = 3, w2 = 1
Implementation
Red = above 90%, Orange = ~ 80%, Yellow = ~ 70%, etc.Dark Grey = ~ 10%, Black ~1%
Implementation
• The probability for each zone was calculated and stored to a lookup table
• The weights used are as follows:w1 = 3, w2 = 1
• w1 is weight for location probability
• w2 is weight for angular probability
Implementation
• The cut-off threshold used were T39 = 0.39 and T30 = 0.30
• These value were acquired by trial and error by manual comparison using visual software
Performance
• “Hacked” the openCV performance evaluation program to incorporate the algorithm
• Runs each setup in parallel to compare original and modified performance
Performance
• 4 Sequences were used for the evaluating the performance
•TestA: 2190 instances
•TestB: 926 instances
•TestC: 208 instances (step size at 10)
•TestD: 2234 instances
Test A
Test A Road Scenario
Test A
Test A Road Scenario
Test A
Test A Road Scenario
Performance for TestARun T39 T30
Original Setup
Hits:1542Miss: 648FA: 1234
FA Rate: 0.563
Hits:1542Miss: 648FA: 1234
FA Rate: 0.563
With Algorithm
Hits:1484Miss: 706FA: 204
FA Rate: 0.093
Hits:1515Miss: 675FA: 250
FA Rate: 0.114
Instances: 2190, Environment: Freeway
Performance for TestA
Performance for TestA
Test B
Test B Road Scenario
Test B
Test B Road Scenario
Test B
Test B Road Scenario
Performance for TestBRun T39 T30
Original Setup
Hits: 242Miss: 683
FA: 73
FA Rate: 0.079
Hits: 242Miss: 683
FA: 73
FA Rate: 0.079
With Algorithm
Hits: 226Miss: 699
FA: 50
FA Rate: 0.053
Hits: 231Miss: 694
FA: 51
FA Rate: 0.055
Instances: 926, Environment: Freeway
Test C
Test C Road Scenario
Test C
Test C Road Scenario
Test C
Test C Road Scenario
Performance for Test CRun T39 T30
Original Setup
Hits: 166Miss: 42
FA: 0
FA Rate: 0.00
Hits: 166Miss: 42
FA: 0
FA Rate: 0.00
With Algorithm
Hits: 166Miss: 42
FA: 0
FA Rate: 0.00
Hits: 165Miss: 43
FA: 0
FA Rate: 0.00
Instances: 208, Environment: Sidestreet
Test D
Test D Road Scenario
Test D
Test D Road Scenario
Test D
Test D Road Scenario
Performance for Test DRun T39 T30
Original Setup
Hits: 151Miss: 2083
FA: 193
FA Rate: 0.087
Hits: 151Miss: 2083
FA: 193
FA Rate: 0.087
With Algorithm
Hits: 16Miss: 2218
FA: 63
FA Rate: 0.028
Hits: 38Miss: 2196
FA: 72
FA Rate: 0.032
Instances: 2231, Environment: Freeway
Next Steps
• Incorporate Size distribution based on distance from vanishing point
• Find solution for “curved road” scenario