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Author |
Daniel Hernandez; Antonio Espinosa; David Vazquez; Antonio Lopez; Juan Carlos Moure |
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Title |
GPU-accelerated real-time stixel computation |
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Conference Article |
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Year |
2017 |
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IEEE Winter Conference on Applications of Computer Vision |
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1054-1062 |
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Keywords |
Autonomous Driving; GPU; Stixel |
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Abstract |
The Stixel World is a medium-level, compact representation of road scenes that abstracts millions of disparity pixels into hundreds or thousands of stixels. The goal of this work is to implement and evaluate a complete multi-stixel estimation pipeline on an embedded, energyefficient, GPU-accelerated device. This work presents a full GPU-accelerated implementation of stixel estimation that produces reliable results at 26 frames per second (real-time) on the Tegra X1 for disparity images of 1024×440 pixels and stixel widths of 5 pixels, and achieves more than 400 frames per second on a high-end Titan X GPU card. |
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Santa Rosa; CA; USA; March 2017 |
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WACV |
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ADAS; 600.118 |
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ADAS @ adas @ HEV2017b |
Serial |
2812 |
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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 |
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Conference Article |
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Year |
2007 |
Publication |
Computer Aided Systems Theory, |
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4739 |
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1105–1112 |
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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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EUROCAST |
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ADAS |
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ADAS @ adas @ SHD2007b |
Serial |
917 |
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Author |
Ferran Diego; Jose Manuel Alvarez; Joan Serrat; Antonio Lopez |
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Title |
Vision-based road detection via on-line video registration |
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Conference Article |
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Year |
2010 |
Publication |
13th Annual International Conference on Intelligent Transportation Systems |
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1135–1140 |
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Keywords |
video alignment; road detection |
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Abstract |
TB6.2
Road segmentation is an essential functionality for supporting advanced driver assistance systems (ADAS) such as road following and vehicle and pedestrian detection. Significant efforts have been made in order to solve this task using vision-based techniques. The major challenge is to deal with lighting variations and the presence of objects on the road surface. In this paper, we propose a new road detection method to infer the areas of the image depicting road surfaces without performing any image segmentation. The idea is to previously segment manually or semi-automatically the road region in a traffic-free reference video record on a first drive. And then to transfer these regions to the frames of a second video sequence acquired later in a second drive through the same road, in an on-line manner. This is possible because we are able to automatically align the two videos in time and space, that is, to synchronize them and warp each frame of the first video to its corresponding frame in the second one. The geometric transform can thus transfer the road region to the present frame on-line. In order to reduce the different lighting conditions which are present in outdoor scenarios, our approach incorporates a shadowless feature space which represents an image in an illuminant-invariant feature space. Furthermore, we propose a dynamic background subtraction algorithm which removes the regions containing vehicles in the observed frames which are within the transferred road region. |
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Madeira Island (Portugal) |
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2153-0009 |
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978-1-4244-7657-2 |
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ITSC |
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ADAS |
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Call Number |
ADAS @ adas @ DAS2010 |
Serial |
1424 |
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Author |
Naveen Onkarappa; Angel Sappa |
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Title |
An Empirical Study on Optical Flow Accuracy Depending on Vehicle Speed |
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Conference Article |
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Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
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1138-1143 |
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Driver assistance and safety systems are getting attention nowadays towards automatic navigation and safety. Optical flow as a motion estimation technique has got major roll in making these systems a reality. Towards this, in the current paper, the suitability of polar representation for optical flow estimation in such systems is demonstrated. Furthermore, the influence of individual regularization terms on the accuracy of optical flow on image sequences of different speeds is empirically evaluated. Also a new synthetic dataset of image sequences with different speeds is generated along with the ground-truth optical flow. |
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Alcalá de Henares |
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IEEE Xplore |
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1931-0587 |
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978-1-4673-2119-8 |
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IV |
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ADAS |
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Call Number |
Admin @ si @ NaS2012 |
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2020 |
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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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1155–1180 |
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Keywords |
road detection |
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Eindhoven (The Netherlands) |
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ADAS;CIC |
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ADAS @ adas @ ALB2008 |
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1045 |
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Author |
Angel Sappa; Fadi Dornaika; David Geronimo; Antonio Lopez |
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Title |
Efficient On-Board Stereo Vision Pose Estimation |
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Conference Article |
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Year |
2007 |
Publication |
Computer Aided Systems Theory, Selected paper from |
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4739 |
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1183–1190 |
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This paper presents an efficient technique for real time estimation of on-board stereo vision system pose. The whole process is performed in the Euclidean space and consists of two stages. Initially, a compact representation of the original 3D data points is computed. Then, a RANSAC based least squares approach is used for fitting a plane to the 3D road points. Fast RANSAC fitting is obtained by selecting points according to a probability distribution function that takes into account the density of points at a given depth. Finally, stereo camera position
and orientation—pose—is computed relative to the road plane. The proposed technique is intended to be used on driver assistance systems for applications such as obstacle or pedestrian detection. A real time performance is reached. Experimental results on several environments and comparisons with a previous work are presented. |
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Las Palmas de Gran Canaria (Spain) |
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EUROCAST |
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ADAS |
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ADAS @ adas @ SDG2007b |
Serial |
916 |
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Author |
Zhijie Fang; Antonio Lopez |
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Title |
Is the Pedestrian going to Cross? Answering by 2D Pose Estimation |
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Conference Article |
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Year |
2018 |
Publication |
IEEE Intelligent Vehicles Symposium |
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1271 - 1276 |
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Our recent work suggests that, thanks to nowadays powerful CNNs, image-based 2D pose estimation is a promising cue for determining pedestrian intentions such as crossing the road in the path of the ego-vehicle, stopping before entering the road, and starting to walk or bending towards the road. This statement is based on the results obtained on non-naturalistic sequences (Daimler dataset), i.e. in sequences choreographed specifically for performing the study. Fortunately, a new publicly available dataset (JAAD) has appeared recently to allow developing methods for detecting pedestrian intentions in naturalistic driving conditions; more specifically, for addressing the relevant question is the pedestrian going to cross? Accordingly, in this paper we use JAAD to assess the usefulness of 2D pose estimation for answering such a question. We combine CNN-based pedestrian detection, tracking and pose estimation to predict the crossing action from monocular images. Overall, the proposed pipeline provides new state-ofthe-art results. |
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IV |
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ADAS; 600.124; 600.116; 600.118 |
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Call Number |
Admin @ si @ FaL2018 |
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3181 |
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Author |
Diego Alejandro Cheda; Daniel Ponsa; Antonio Lopez |
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Title |
Camera Egomotion Estimation in the ADAS Context |
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Conference Article |
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Year |
2010 |
Publication |
13th International IEEE Annual Conference on Intelligent Transportation Systems |
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1415–1420 |
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Camera-based Advanced Driver Assistance Systems (ADAS) have concentrated many research efforts in the last decades. Proposals based on monocular cameras require the knowledge of the camera pose with respect to the environment, in order to reach an efficient and robust performance. A common assumption in such systems is considering the road as planar, and the camera pose with respect to it as approximately known. However, in real situations, the camera pose varies along time due to the vehicle movement, the road slope, and irregularities on the road surface. Thus, the changes in the camera position and orientation (i.e., the egomotion) are critical information that must be estimated at every frame to avoid poor performances. This work focuses on egomotion estimation from a monocular camera under the ADAS context. We review and compare egomotion methods with simulated and real ADAS-like sequences. Basing on the results of our experiments, we show which of the considered nonlinear and linear algorithms have the best performance in this domain. |
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Madeira Island (Portugal) |
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2153-0009 |
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978-1-4244-7657-2 |
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ITSC |
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ADAS |
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ADAS @ adas @ CPL2010 |
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1425 |
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Author |
Mohammad Rouhani; Angel Sappa |
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Title |
A Fast accurate Implicit Polynomial Fitting Approach |
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Conference Article |
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2010 |
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17th IEEE International Conference on Image Processing |
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1429–1432 |
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This paper presents a novel hybrid approach that combines state of the art fitting algorithms: algebraic-based and geometric-based. It consists of two steps; first, the 3L algorithm is used as an initialization and then, the obtained result, is improved through a geometric approach. The adopted geometric approach is based on a distance estimation that avoids costly search for the real orthogonal distance. Experimental results are presented as well as quantitative comparisons. |
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Hong-Kong |
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1522-4880 |
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978-1-4244-7992-4 |
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ICIP |
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ADAS |
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ADAS @ adas @ RoS2010b |
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1359 |
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Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat |
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Title |
Photometric Stereo through and Adapted Alternation Approach |
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2008 |
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IEEE International Conference on Image Processing, |
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1500–1503 |
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San Diego; CA; USA |
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ADAS |
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ADAS @ adas @ JSL2008d |
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1016 |
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