Method

FCN_simplify [FCNS]
[Anonymous Submission]

Submitted on 22 Mar. 2016 12:52 by
[Anonymous Submission]

Running time:6 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
FCN simplify, first baseline model.
Parameters:
VGG16
Latex Bibtex:

Evaluation in Bird's Eye View


Benchmark MaxF AP PRE REC FPR FNR
UM_ROAD 82.97 % 87.01 % 80.84 % 85.21 % 9.20 % 14.79 %
UMM_ROAD 91.28 % 93.68 % 90.51 % 92.07 % 10.61 % 7.93 %
UU_ROAD 80.20 % 84.90 % 77.92 % 82.62 % 7.63 % 17.38 %
URBAN_ROAD 85.93 % 89.80 % 84.59 % 87.32 % 8.76 % 12.68 %
UM_LANE 76.31 % 81.57 % 77.88 % 74.81 % 3.74 % 25.19 %
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Behavior Evaluation


Benchmark PRE-20 F1-20 HR-20 PRE-30 F1-30 HR-30 PRE-40 F1-40 HR-40
UM_LANE 98.72 % 98.29 % 97.58 % 94.67 % 90.59 % 87.28 % 82.35 % 66.67 % 64.29 %
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Road/Lane Detection

The following plots show precision/recall curves for the bird's eye view evaluation.



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Distance-dependent Behavior Evaluation

The following plots show the F1 score/Precision/Hitrate with respect to the longitudinal distance which has been used for evaluation.



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Visualization of Results

The following images illustrate the performance of the method qualitatively on a couple of test images. We first show results in the perspective image, followed by evaluation in bird's eye view. Here, red denotes false negatives, blue areas correspond to false positives and green represents true positives.



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