Library EntranceLibrary WalkSidewalk01sidewalk2
Sidewalk02... Scene Description - [html] [pdf]

Congestion
Level Experiments

Oblique Angle
Still

8 8 8 Experiment Accuracy
Martin NN = 56%
Nearest-neighbor classifier using Martin distance.
State KL NN = 54%
Nearest-neighbor classifier using state KL divergence
State KL SVM = 57%
SVM classifier using state KL kernel
Image KL NN = 54%
Nearest-neighbor classifier using image KL divergence
Image KL SVM = 55%
SVM classifier using image KL kernel
Description
In this experiment, we attempt to discriminate between three congestion levels of pedsetrian traffic using still clips at an oblique angle Location: Bridge above walkway in Marshall College, UC, San Diego.
Clips: High Flow
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Clips: Medium Flow
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1 2 3 4 5 6
mp4 (mpeg4)
1 2 3 4 5 6
Clips: Low Flow
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1 2 3 4
mp4 (mpeg4)
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Front Angle
Still
8 8 8 Experiment Accuracy
 
Description
In this experiment, we attempt to discriminate between three congestion levels of pedsetrian traffic using still clips at a front angle Location: walkway in Marshall College, UC, San Diego.
Clips: High Flow
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Clips: Medium Flow
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1 2 3
mov (h.264)
1 2 3
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1 2 3
Clips: Low Flow
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1 2
mov (h.264)
1 2
mp4 (mpeg4)
1 2
 
Side Angle
Still
8 8   Experiment Accuracy
 
Description
In this experiment, we attempt to discriminate between three congestion levels of pedsetrian traffic using still clips at a side angle Location: walkway in Marshall College, UC, San Diego.
Clips: Medium Flow
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divx
1 2 3
mov (h.264)
1 2 3
mp4 (mpeg4)
1 2 3
Clips: Low Flow
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mov (h.264)
1 2 3 4
mp4 (mpeg4)
1 2 3 4
 
 
Front Angle
Pan
pan     Experiment Accuracy
 
Description
Nothing yet.
Clips: Low Flow
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