Method

random_forests [RFH]


Submitted on 31 Jan. 2016 17:31 by
Mujtaba hasan (IIT_Delhi)

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

Method Description:
A novel entropy update mechanism of random forest implemented using CUDA and a novel color difference based features of neighboring regions are used.
Parameters:
10 trees with max depth 5
Latex Bibtex:

Evaluation in Bird's Eye View


Benchmark MaxF AP PRE REC FPR FNR
UM_ROAD 76.18 % 61.64 % 68.38 % 86.00 % 18.12 % 14.00 %
UMM_ROAD 89.34 % 79.11 % 81.78 % 98.42 % 24.10 % 1.58 %
UU_ROAD 71.69 % 55.20 % 62.01 % 84.96 % 16.96 % 15.04 %
URBAN_ROAD 80.94 % 69.22 % 72.59 % 91.46 % 19.03 % 8.54 %
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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