| Records |
| Author |
German Ros |
| Title |
Visual SLAM for Driverless Cars: An Initial Survey |
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Report |
| Year |
2012 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
170 |
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Thesis |
Master's thesis |
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ADAS |
Approved |
no |
| Call Number |
Admin @ si @ Ros2012c |
Serial |
2414 |
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| Author |
Xu Hu |
| Title |
Real-Time Part Based Models for Object Detection |
Type |
Report |
| Year |
2012 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
171 |
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Master's thesis |
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ADAS;ISE |
Approved |
no |
| Call Number |
Admin @ si @ Hu2012 |
Serial |
2415 |
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| Author |
Nuria Cirera |
| Title |
Recognition of Handwritten Historical Documents |
Type |
Report |
| Year |
2012 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
174 |
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Thesis |
Master's thesis |
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DAG |
Approved |
no |
| Call Number |
Admin @ si @ Cir2012 |
Serial |
2416 |
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| Author |
Cristhian A. Aguilera-Carrasco |
| Title |
Evaluation of feature detectors and descriptors in VISIBLE-LWIR cross-spectral imaging |
Type |
Report |
| Year |
2014 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
177 |
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| Keywords |
Multi-spectral; Cross-spectral; Visible-LWIR imaging; Multimodal. |
| Abstract |
This thesis evaluates the performance of different state-of-art feature detectors and descriptors algorithms in the Visible-LWIR cross-spectral scenario. The focus is to determine if current detector and descriptor algorithms can be used to match features between the LWIR spectrum and the visible spectrum in applications such as, visual odometry, object recognition, image registration and stereo vision. An outdoor cross-spectral dataset was created to evaluate the suitability of the different algorithms. The results
show that the tested algorithms are not suitable to the task of matching features across different spectra. The repeatability ratio was smaller than the 30 percent in the best case and in general matched features were not accurate located. Additionally, these results also suggest that is necessary to create new algorithms that take into account the nature of the different spectra, describing characteristics that exist in both spectra such as discontinuities. |
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Thesis |
Master's thesis |
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ADAS; 600.076 |
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no |
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Admin @ si @Agu2014 |
Serial |
2526 |
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| Author |
Antonio Esteban Lansaque |
| Title |
3D reconstruction and recognition using structured ligth |
Type |
Report |
| Year |
2014 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
179 |
Issue |
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| Abstract |
This work covers the problem of 3D reconstruction, recognition and 6DOF pose estimation. The goal of this project is to reconstruct a 3D scene and to align an object model of the industrial pieces onto the reconstructed scene. The reconstruction algorithm is based on stereo techniques and the recognition algorithm is based on SHOT descriptors computed on a set of uniform keypoints. Correspondences are used to estimate a first 6DOF transformation that maps the model onto the scene and then ICP algorithm is used to refine the transformation. In order to check the effectiveness of the proposed algorithm, several experiments were performed. These experiments were conducted on a lab environment in order to get results under the same conditions in all of them. Although obtained results are not real time results, the proposed algorithm ends up with high rates of object recognition. |
| Address |
UAB; September 2014 |
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Master's thesis |
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| Notes |
IAM; 600.075 |
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no |
| Call Number |
Admin @ si @ Est2014 |
Serial |
2578 |
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| Author |
Ricard Balague |
| Title |
Exploring the combination of color cues for intrinsic image decomposition |
Type |
Report |
| Year |
2014 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
178 |
Issue |
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| Abstract |
Intrinsic image decomposition is a challenging problem that consists in separating an image into its physical characteristics: reflectance and shading. This problem can be solved in different ways, but most methods have combined information from several visual cues. In this work we describe an extension of an existing method proposed by Serra et al. which considers two color descriptors and combines them by means of a Markov Random Field. We analyze in depth the weak points of the method and we explore more possibilities to use in both descriptors. The proposed extension depends on the combination of the cues considered to overcome some of the limitations of the original method. Our approach is tested on the MIT dataset and Beigpour et al. dataset, which contain images of real objects acquired under controlled conditions and synthetic images respectively, with their corresponding ground truth. |
| Address |
UAB; September 2014 |
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Master's thesis |
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| Notes |
CIC; 600.074 |
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no |
| Call Number |
Admin @ si @ Bal2014 |
Serial |
2579 |
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| Author |
Sebastian Ramos |
| Title |
Vision-based Detection of Road Hazards for Autonomous Driving |
Type |
Report |
| Year |
2014 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Address |
UAB; September 2014 |
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Master's thesis |
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| Notes |
ADAS; 600.076 |
Approved |
no |
| Call Number |
Admin @ si @ Ram2014 |
Serial |
2580 |
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| Author |
Daniel Hernandez; Alejandro Chacon; Antonio Espinosa; David Vazquez; Juan Carlos Moure; Antonio Lopez |
| Title |
Stereo Matching using SGM on the GPU |
Type |
Report |
| Year |
2016 |
Publication |
Programming and Tuning Massively Parallel Systems |
Abbreviated Journal |
PUMPS |
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| Keywords |
CUDA; Stereo; Autonomous Vehicle |
| Abstract |
Dense, robust and real-time computation of depth information from stereo-camera systems is a computationally demanding requirement for robotics, advanced driver assistance systems (ADAS) and autonomous vehicles. Semi-Global Matching (SGM) is a widely used algorithm that propagates consistency constraints along several paths across the image. This work presents a real-time system producing reliable disparity estimation results on the new embedded energy efficient GPU devices. Our design runs on a Tegra X1 at 42 frames per second (fps) for an image size of 640x480, 128 disparity levels, and using 4 path directions for the SGM method. |
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PUMPS |
| Notes |
ADAS; 600.085; 600.087; 600.076 |
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no |
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ADAS @ adas @ HCE2016b |
Serial |
2776 |
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