Method

random_forests [RNF]


Submitted on 31 Jan. 2016 16:45 by
mujtaba hasan (iit delhi)

Running time:.5 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
random forests on histogram of novel color difference based features
Parameters:
number of trees=5, max depth=18 and
Latex Bibtex:

Evaluation in Bird's Eye View


Benchmark MaxF AP PRE REC FPR FNR
UM_ROAD 83.71 % 72.64 % 88.14 % 79.71 % 4.89 % 20.29 %
UMM_ROAD 83.87 % 78.26 % 84.02 % 83.72 % 17.51 % 16.28 %
UU_ROAD 75.36 % 63.87 % 78.61 % 72.37 % 6.42 % 27.63 %
URBAN_ROAD 81.79 % 70.72 % 83.92 % 79.77 % 8.42 % 20.23 %
This table as LaTeX

Behavior Evaluation


This table as LaTeX

Road/Lane Detection

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


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.


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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