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Author Daniel Ponsa; Antonio Lopez; Felipe Lumbreras; Joan Serrat; T. Graf
Title (down) 3D Vehicle Sensor based on Monocular Vision Type Miscellaneous
Year 2005 Publication Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems, 1096–1101, ISBN:0–7803–9216–7 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Vienna (Austria)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number ADAS @ adas @ PLL2005 Serial 614
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Author Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu
Title (down) 3D Texton Spaces for color-texture retrieval Type Conference Article
Year 2010 Publication 7th International Conference on Image Analysis and Recognition Abbreviated Journal
Volume 6111 Issue Pages 354–363
Keywords
Abstract Color and texture are visual cues of different nature, their integration in an useful visual descriptor is not an easy problem. One way to combine both features is to compute spatial texture descriptors independently on each color channel. Another way is to do the integration at the descriptor level. In this case the problem of normalizing both cues arises. In this paper we solve the latest problem by fusing color and texture through distances in texton spaces. Textons are the attributes of image blobs and they are responsible for texture discrimination as defined in Julesz’s Texton theory. We describe them in two low-dimensional and uniform spaces, namely, shape and color. The dissimilarity between color texture images is computed by combining the distances in these two spaces. Following this approach, we propose our TCD descriptor which outperforms current state of art methods in the two different approaches mentioned above, early combination with LBP and late combination with MPEG-7. This is done on an image retrieval experiment over a highly diverse texture dataset from Corel.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor A.C. Campilho and M.S. Kamel
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-13771-6 Medium
Area Expedition Conference ICIAR
Notes CIC Approved no
Call Number CAT @ cat @ ASV2010a Serial 1325
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Author Debora Gil; F. Javier Sanchez; Gloria Fernandez Esparrach; Jorge Bernal
Title (down) 3D Stable Spatio-temporal Polyp Localization in Colonoscopy Videos Type Book Chapter
Year 2015 Publication Computer-Assisted and Robotic Endoscopy. Revised selected papers of Second International Workshop, CARE 2015, Held in Conjunction with MICCAI 2015 Abbreviated Journal
Volume 9515 Issue Pages 140-152
Keywords Colonoscopy, Polyp Detection, Polyp Localization, Region Extraction, Watersheds
Abstract Computational intelligent systems could reduce polyp miss rate in colonoscopy for colon cancer diagnosis and, thus, increase the efficiency of the procedure. One of the main problems of existing polyp localization methods is a lack of spatio-temporal stability in their response. We propose to explore the response of a given polyp localization across temporal windows in order to select
those image regions presenting the highest stable spatio-temporal response.
Spatio-temporal stability is achieved by extracting 3D watershed regions on the
temporal window. Stability in localization response is statistically determined by analysis of the variance of the output of the localization method inside each 3D region. We have explored the benefits of considering spatio-temporal stability in two different tasks: polyp localization and polyp detection. Experimental results indicate an average improvement of 21:5% in polyp localization and 43:78% in polyp detection.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CARE
Notes IAM; MV; 600.075 Approved no
Call Number Admin @ si @ GSF2015 Serial 2733
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Author Shun Yao; Fei Yang; Yongmei Cheng; Mikhail Mozerov
Title (down) 3D Shapes Local Geometry Codes Learning with SDF Type Conference Article
Year 2021 Publication International Conference on Computer Vision Workshops Abbreviated Journal
Volume Issue Pages 2110-2117
Keywords
Abstract A signed distance function (SDF) as the 3D shape description is one of the most effective approaches to represent 3D geometry for rendering and reconstruction. Our work is inspired by the state-of-the-art method DeepSDF [17] that learns and analyzes the 3D shape as the iso-surface of its shell and this method has shown promising results especially in the 3D shape reconstruction and compression domain. In this paper, we consider the degeneration problem of reconstruction coming from the capacity decrease of the DeepSDF model, which approximates the SDF with a neural network and a single latent code. We propose Local Geometry Code Learning (LGCL), a model that improves the original DeepSDF results by learning from a local shape geometry of the full 3D shape. We add an extra graph neural network to split the single transmittable latent code into a set of local latent codes distributed on the 3D shape. Mentioned latent codes are used to approximate the SDF in their local regions, which will alleviate the complexity of the approximation compared to the original DeepSDF. Furthermore, we introduce a new geometric loss function to facilitate the training of these local latent codes. Note that other local shape adjusting methods use the 3D voxel representation, which in turn is a problem highly difficult to solve or even is insolvable. In contrast, our architecture is based on graph processing implicitly and performs the learning regression process directly in the latent code space, thus make the proposed architecture more flexible and also simple for realization. Our experiments on 3D shape reconstruction demonstrate that our LGCL method can keep more details with a significantly smaller size of the SDF decoder and outperforms considerably the original DeepSDF method under the most important quantitative metrics.
Address VIRTUAL; October 2021
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference ICCVW
Notes LAMP Approved no
Call Number Admin @ si @ YYC2021 Serial 3681
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Author Jose Manuel Alvarez; Theo Gevers; Antonio Lopez
Title (down) 3D Scene Priors for Road Detection Type Conference Article
Year 2010 Publication 23rd IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal
Volume Issue Pages 57–64
Keywords road detection
Abstract Vision-based road detection is important in different areas of computer vision such as autonomous driving, car collision warning and pedestrian crossing detection. However, current vision-based road detection methods are usually based on low-level features and they assume structured roads, road homogeneity, and uniform lighting conditions. Therefore, in this paper, contextual 3D information is used in addition to low-level cues. Low-level photometric invariant cues are derived from the appearance of roads. Contextual cues used include horizon lines, vanishing points, 3D scene layout and 3D road stages. Moreover, temporal road cues are included. All these cues are sensitive to different imaging conditions and hence are considered as weak cues. Therefore, they are combined to improve the overall performance of the algorithm. To this end, the low-level, contextual and temporal cues are combined in a Bayesian framework to classify road sequences. Large scale experiments on road sequences show that the road detection method is robust to varying imaging conditions, road types, and scenarios (tunnels, urban and highway). Further, using the combined cues outperforms all other individual cues. Finally, the proposed method provides highest road detection accuracy when compared to state-of-the-art methods.
Address San Francisco; CA; USA; June 2010
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1063-6919 ISBN 978-1-4244-6984-0 Medium
Area Expedition Conference CVPR
Notes ADAS;ISE Approved no
Call Number ADAS @ adas @ AGL2010a Serial 1302
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Author Fernando Vilariño
Title (down) 3D Scanning of Capitals at Library Living Lab Type Book Whole
Year 2019 Publication “Living Lab Projects 2019”. ENoLL. Abbreviated Journal
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Abstract
Address
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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Area Expedition Conference
Notes MV; DAG; 600.140; 600.121;SIAI Approved no
Call Number Admin @ si @ Vil2019c Serial 3463
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Author Petia Radeva; M. Scoccianti
Title (down) 3D Reconstruction of Abdominal Aortic Aneurysm Type Miscellaneous
Year 2000 Publication Elsevier Science B.V., Ed. H.U. Lemke, M.W. Vannier, K. Inamura, A.G.Farman and K.Doi, CARS 2000, pp.1014, ISBN:0–444–50536–9 Abbreviated Journal
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Abstract
Address San Francisco, USA
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ RaS2000 Serial 439
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Author Petia Radeva; Cristina Cañero; Juan J. Villanueva; J. Mauri; E Fernandez-Nofrerias
Title (down) 3D Reconstruction of a Stent by Deformable Models. Type Miscellaneous
Year 2001 Publication Proceedings of the IASTED International Conference, Visualization, Imaging and Image Processing, 417–422. Abbreviated Journal
Volume Issue Pages
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Abstract
Address Marbella.
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ RCV2001 Serial 158
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Author Antonio Esteban Lansaque
Title (down) 3D reconstruction and recognition using structured ligth Type Report
Year 2014 Publication CVC Technical Report Abbreviated Journal
Volume 179 Issue Pages
Keywords
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
Corporate Author Thesis Master's thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes IAM; 600.075 Approved no
Call Number Admin @ si @ Est2014 Serial 2578
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Author Daniel Hernandez; Antonio Espinosa; David Vazquez; Antonio Lopez; Juan C. Moure
Title (down) 3D Perception With Slanted Stixels on GPU Type Journal Article
Year 2021 Publication IEEE Transactions on Parallel and Distributed Systems Abbreviated Journal TPDS
Volume 32 Issue 10 Pages 2434-2447
Keywords Daniel Hernandez-Juarez; Antonio Espinosa; David Vazquez; Antonio M. Lopez; Juan C. Moure
Abstract This article presents a GPU-accelerated software design of the recently proposed model of Slanted Stixels, which represents the geometric and semantic information of a scene in a compact and accurate way. We reformulate the measurement depth model to reduce the computational complexity of the algorithm, relying on the confidence of the depth estimation and the identification of invalid values to handle outliers. The proposed massively parallel scheme and data layout for the irregular computation pattern that corresponds to a Dynamic Programming paradigm is described and carefully analyzed in performance terms. Performance is shown to scale gracefully on current generation embedded GPUs. We assess the proposed methods in terms of semantic and geometric accuracy as well as run-time performance on three publicly available benchmark datasets. Our approach achieves real-time performance with high accuracy for 2048 × 1024 image sizes and 4 × 4 Stixel resolution on the low-power embedded GPU of an NVIDIA Tegra Xavier.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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Area Expedition Conference
Notes ADAS; 600.124; 600.118 Approved no
Call Number Admin @ si @ HEV2021 Serial 3561
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Author Gabriel Villalonga; Sebastian Ramos; German Ros; David Vazquez; Antonio Lopez
Title (down) 3d Pedestrian Detection via Random Forest Type Miscellaneous
Year 2014 Publication European Conference on Computer Vision Abbreviated Journal
Volume Issue Pages 231-238
Keywords Pedestrian Detection
Abstract Our demo focuses on showing the extraordinary performance of our novel 3D pedestrian detector along with its simplicity and real-time capabilities. This detector has been designed for autonomous driving applications, but it can also be applied in other scenarios that cover both outdoor and indoor applications.
Our pedestrian detector is based on the combination of a random forest classifier with HOG-LBP features and the inclusion of a preprocessing stage based on 3D scene information in order to precisely determinate the image regions where the detector should search for pedestrians. This approach ends up in a high accurate system that runs real-time as it is required by many computer vision and robotics applications.
Address Zurich; suiza; September 2014
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference ECCV-Demo
Notes ADAS; 600.076 Approved no
Call Number Admin @ si @ VRR2014 Serial 2570
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Author Fadi Dornaika; Angel Sappa
Title (down) 3D Motion from Image Derivatives using the Least Trimmed Square Regression Type Book Chapter
Year 2006 Publication International Workshop on Intelligent Computing in Pattern Analysis/Synthesis (IWICPAS´06), LNCS 4153: 76–84 Abbreviated Journal
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Keywords
Abstract
Address Xi'an (China)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number ADAS @ adas @ DoS2006b Serial 690
Permanent link to this record
 
 
Author Wenjuan Gong
Title (down) 3D Motion Data aided Human Action Recognition and Pose Estimation Type Book Whole
Year 2013 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal
Volume Issue Pages
Keywords
Abstract In this work, we explore human action recognition and pose estimation prob-
lems. Different from traditional works of learning from 2D images or video
sequences and their annotated output, we seek to solve the problems with ad-
ditional 3D motion capture information, which helps to fill the gap between 2D
image features and human interpretations.
We first compare two different schools of approaches commonly used for 3D
pose estimation from 2D pose configuration: modeling and learning methods.
By looking into experiments results and considering our problems, we fixed a
learning method as the following approaches to do pose estimation. We then
establish a framework by adding a module of detecting 2D pose configuration
from images with varied background, which widely extend the application of
the approach. We also seek to directly estimate 3D poses from image features,
instead of estimating 2D poses as a intermediate module. We explore a robust
input feature, which combined with the proposed distance measure, provides
a solution for noisy or corrupted inputs. We further utilize the above method
to estimate weak poses,which is a concise representation of the original poses
by using dimension deduction technologies, from image features. Weak pose
space is where we calculate vocabulary and label action types using a bog of
words pipeline. Temporal information of an action is taken into consideration by
considering several consecutive frames as a single unit for computing vocabulary
and histogram assignments.
Address Barcelona
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Editor Jordi Gonzalez;Xavier Roca
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ISE Approved no
Call Number Admin @ si @ Gon2013 Serial 2279
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Author David Rotger; Cristina Cañero; Petia Radeva; J. Mauri; E. Fernandez; A. Tovar; V. Valle
Title (down) 3D Interactive Visualization and Volumetric Measurements of Coronary Vessels in IVUS. Type Miscellaneous
Year 2001 Publication Proceedings of the IX Spanish Symposium on Pattern Recognition and Image Analysis, 1:151–156. Abbreviated Journal
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Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference
Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ RCR2001a Serial 156
Permanent link to this record
 
 
Author Angel Sappa; Niki Aifanti; Sotiris Malassiotis; Michael G. Strintzis
Title (down) 3D Human Walking Modelling Type Book Whole
Year 2004 Publication Articulated Motion and Deformable Objects, Third International Workshop, (AMDO 2004), Lecture Notes in Computer Science, F.J. Perales, B.A. Draper (Eds.), 3179:111–122 Abbreviated Journal
Volume Issue Pages
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Abstract
Address Springer-Verlag, Berlin, Heidelberg
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number ADAS @ adas @ SAM2004b Serial 494
Permanent link to this record