Method

Supervised DPM learning based on C8B1 feats [st] [DPM-C8B1]


Submitted on 28 Apr. 2014 20:20 by
J. Javier Yebes (University of Alcalá)

Running time:15 s
Environment:4 cores @ 2.5 Ghz (Matlab + C/C++)

Method Description:
Time varies depending on the number of model components
Cars: 16 viewpoints ~ 28 seconds
Pedestrians: 8 viewpoints ~ 13 seconds
Cyclists: 4 viewpoints ~ 7 seconds

Parameters:
C=0.001
Latex Bibtex:
@article{Yebes2015SENSORS,
author = {J. Javier Yebes and Luis M. Bergasa and M.A. García-Garrido},
title = {{Visual Object Recognition with 3D-Aware Features in KITTI Urban Scenes}},
journal = {Sensors},
volume = {15},
number = {4},
pages = {9228--9250},
issn = {1424-8220},
year = {2015}
}

@inproceedings{ref:Yebes14iv,
author = {J.Javier Yebes and Luis M. Bergasa and Roberto Arroyo and Alberto Lázaro},
title = {{Supervised learning and evaluation of KITTI's cars detector with DPM}},
booktitle = IV,
pages = {768-773},
isbn = {978-1-4799-3637-3},
address = {Detroit, USA},
month = {June},
year = {2014}
}

Detailed Results

Object detection and orientation estimation results. Results for object detection are given in terms of average precision (AP) and results for joint object detection and orientation estimation are provided in terms of average orientation similarity (AOS).


Benchmark Easy Moderate Hard
Car (Detection) 74.95 % 60.99 % 47.16 %
Car (Orientation) 59.53 % 50.32 % 39.22 %
Pedestrian (Detection) 38.96 % 29.03 % 25.61 %
Pedestrian (Orientation) 31.08 % 23.37 % 20.72 %
Cyclist (Detection) 43.28 % 29.04 % 26.20 %
Cyclist (Orientation) 27.16 % 19.25 % 17.95 %
This table as LaTeX


2D object detection results.
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Orientation estimation results.
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2D object detection results.
This figure as: png eps pdf txt gnuplot



Orientation estimation results.
This figure as: png eps pdf txt gnuplot



2D object detection results.
This figure as: png eps pdf txt gnuplot



Orientation estimation results.
This figure as: png eps pdf txt gnuplot




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