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Author |
Jose Manuel Alvarez |
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Title |
Combining Context and Appearance for Road Detection |
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Book Whole |
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Year |
2010 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Abstract |
Road traffic crashes have become a major cause of death and injury throughout the world.
Hence, in order to improve road safety, the automobile manufacture is moving towards the
development of vehicles with autonomous functionalities such as keeping in the right lane, safe distance keeping between vehicles or regulating the speed of the vehicle according to the traffic conditions. A key component of these systems is vision–based road detection that aims to detect the free road surface ahead the moving vehicle. Detecting the road using a monocular vision system is very challenging since the road is an outdoor scenario imaged from a mobile platform. Hence, the detection algorithm must be able to deal with continuously changing imaging conditions such as the presence ofdifferent objects (vehicles, pedestrians), different environments (urban, highways, off–road), different road types (shape, color), and different imaging conditions (varying illumination, different viewpoints and changing weather conditions). Therefore, in this thesis, we focus on vision–based road detection using a single color camera. More precisely, we first focus on analyzing and grouping pixels according to their low–level properties. In this way, two different approaches are presented to exploit
color and photometric invariance. Then, we focus the research of the thesis on exploiting context information. This information provides relevant knowledge about the road not using pixel features from road regions but semantic information from the analysis of the scene.
In this way, we present two different approaches to infer the geometry of the road ahead
the moving vehicle. Finally, we focus on combining these context and appearance (color)
approaches to improve the overall performance of road detection algorithms. The qualitative and quantitative results presented in this thesis on real–world driving sequences show that the proposed method is robust to varying imaging conditions, road types and scenarios going beyond the state–of–the–art. |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Editor |
Antonio Lopez;Theo Gevers |
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978-84-937261-8-8 |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ Alv2010 |
Serial |
1454 |
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Author |
Zhijie Fang |
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Title |
Behavior understanding of vulnerable road users by 2D pose estimation |
Type |
Book Whole |
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Year |
2019 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Anticipating the intentions of vulnerable road users (VRUs) such as pedestrians
and cyclists can be critical for performing safe and comfortable driving maneuvers. This is the case for human driving and, therefore, should be taken into account by systems providing any level of driving assistance, i.e. from advanced driver assistant systems (ADAS) to fully autonomous vehicles (AVs). In this PhD work, we show how the latest advances on monocular vision-based human pose estimation, i.e. those relying on deep Convolutional Neural Networks (CNNs), enable to recognize the intentions of such VRUs. In the case of cyclists, we assume that they follow the established traffic codes to indicate future left/right turns and stop maneuvers with arm signals. In the case of pedestrians, no indications can be assumed a priori. Instead, we hypothesize that the walking pattern of a pedestrian can allow us to determine if he/she has the intention of crossing the road in the path of the egovehicle, so that the ego-vehicle must maneuver accordingly (e.g. slowing down or stopping). In this PhD work, we show how the same methodology can be used for recognizing pedestrians and cyclists’ intentions. For pedestrians, we perform experiments on the publicly available Daimler and JAAD datasets. For cyclists, we did not found an analogous dataset, therefore, we created our own one by acquiring
and annotating corresponding video-sequences which we aim to share with the
research community. Overall, the proposed pipeline provides new state-of-the-art results on the intention recognition of VRUs. |
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Address |
May 2019 |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Editor |
Antonio Lopez;David Vazquez |
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978-84-948531-6-6 |
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Notes |
ADAS; 600.118 |
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no |
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Call Number |
Admin @ si @ Fan2019 |
Serial |
3388 |
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Author |
Sebastian Ramos |
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Title |
Vision-based Detection of Road Hazards for Autonomous Driving |
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Report |
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Year |
2014 |
Publication |
CVC Technical Report |
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Address |
UAB; September 2014 |
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Master's thesis |
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Notes |
ADAS; 600.076 |
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no |
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Call Number |
Admin @ si @ Ram2014 |
Serial |
2580 |
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Author |
Jose Manuel Alvarez |
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Title |
On-Board Road Surface Segmentation |
Type |
Report |
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Year |
2007 |
Publication |
CVC Technical Report #108 |
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CVC (UAB) |
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Notes |
ADAS |
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no |
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Call Number |
Admin @ si @ Alv2007 |
Serial |
820 |
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Author |
Angel Sappa; Rosa Herrero; Fadi Dornaika; David Geronimo; Antonio Lopez |
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Title |
Road Approximation in Euclidean and v-Disparity Space: A Comparative Study |
Type |
Conference Article |
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Year |
2007 |
Publication |
Computer Aided Systems Theory, |
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Volume |
4739 |
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Pages |
1105–1112 |
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Abstract |
This paper presents a comparative study between two road approximation techniques—planar surfaces—from stereo vision data. The first approach is carried out in the v-disparity space and is based on a voting scheme, the Hough transform. The second one consists in computing the best fitting plane for the whole 3D road data points, directly in the Euclidean space, by using least squares fitting. The comparative study is initially performed over a set of different synthetic surfaces
(e.g., plane, quadratic surface, cubic surface) digitized by a virtual stereo head; then real data obtained with a commercial stereo head are used. The comparative study is intended to be used as a criterion for fining the best technique according to the road geometry. Additionally, it highlights common problems driven from a wrong assumption about the scene’s prior knowledge. |
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Las Palmas de Gran Canaria (Spain) |
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Conference |
EUROCAST |
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Notes |
ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ SHD2007b |
Serial |
917 |
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Permanent link to this record |
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Author |
Angel Sappa; Rosa Herrero; Fadi Dornaika; David Geronimo; Antonio Lopez |
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Title |
Road Approximation in Euclidean and v-Disparity Space: A Comparative Study |
Type |
Conference Article |
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Year |
2007 |
Publication |
EUROCAST2007, Workshop on Cybercars and Intelligent Vehicles |
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Pages |
368–369 |
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Abstract |
This paper presents a comparative study between two road approximation techniques—planar surfaces—from stereo vision data. The first approach is carried out in the v-disparity space and is based on a voting scheme, the Hough transform. The second one consists in computing the best fitting plane for the whole 3D road data points, directly in the Euclidean space, by using least squares fitting. The comparative study is initially performed over a set of different synthetic surfaces
(e.g., plane, quadratic surface, cubic surface) digitized by a virtual stereo head; then real data obtained with a commercial stereo head are used. The comparative study is intended to be used as a criterion for fining the best technique according to the road geometry. Additionally, it highlights common problems driven from a wrong assumption about the scene’s prior knowledge. |
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Las Palmas de Gran Canaria (Spain) |
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Notes |
ADAS |
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Call Number |
ADAS @ adas @ SHD2007a |
Serial |
936 |
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Permanent link to this record |
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Author |
Jose Manuel Alvarez; Antonio Lopez; Ramon Baldrich |
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Title |
Shadow Resistant Road Segmentation from a Mobile Monocular System |
Type |
Conference Article |
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Year |
2007 |
Publication |
3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4477:9–16 |
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Keywords |
road detection |
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Address |
Gerona (Spain) |
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Notes |
ADAS;CIC |
Approved |
no |
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Call Number |
ADAS @ adas @ ALB2007 |
Serial |
943 |
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Author |
Jose Manuel Alvarez; Antonio Lopez; Ramon Baldrich |
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Title |
Illuminant Invariant Model-Based Road Segmentation |
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Conference Article |
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Year |
2008 |
Publication |
IEEE Intelligent Vehicles Symposium, |
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Pages |
1155–1180 |
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Keywords |
road detection |
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Address |
Eindhoven (The Netherlands) |
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Notes |
ADAS;CIC |
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no |
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Call Number |
ADAS @ adas @ ALB2008 |
Serial |
1045 |
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Author |
Jose Manuel Alvarez; Antonio Lopez |
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Title |
Novel Index for Objective Evaluation of Road Detection Algorithms |
Type |
Conference Article |
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Year |
2008 |
Publication |
Intelligent Transportation Systems. 11th International IEEE Conference on, |
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815–820 |
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road detection |
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Address |
Beijing (Xina) |
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ITSC |
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Notes |
ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ AlL2008 |
Serial |
1074 |
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Author |
Jose Manuel Alvarez; Antonio Lopez |
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Title |
Model-based road detection using shadowless features and on-line learning |
Type |
Miscellaneous |
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Year |
2009 |
Publication |
BMVA one–day technical meeting on vision for automotive applications |
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road detection |
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London, UK |
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ADAS |
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Call Number |
ADAS @ adas @ AlA2009 |
Serial |
1272 |
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