| Records |
| Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez |
| Title |
Pedestrian Candidates Generation using Monocular Cues |
Type |
Conference Article |
| Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
Abbreviated Journal |
|
| Volume |
|
Issue  |
|
Pages |
7-12 |
| Keywords |
pedestrian detection |
| Abstract |
Common techniques for pedestrian candidates generation (e.g., sliding window approaches) are based on an exhaustive search over the image. This implies that the number of windows produced is huge, which translates into a significant time consumption in the classification stage. In this paper, we propose a method that significantly reduces the number of windows to be considered by a classifier. Our method is a monocular one that exploits geometric and depth information available on single images. Both representations of the world are fused together to generate pedestrian candidates based on an underlying model which is focused only on objects standing vertically on the ground plane and having certain height, according with their depths on the scene. We evaluate our algorithm on a challenging dataset and demonstrate its application for pedestrian detection, where a considerable reduction in the number of candidate windows is reached. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
IEEE Xplore |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1931-0587 |
ISBN |
978-1-4673-2119-8 |
Medium |
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| Area |
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Expedition |
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Conference |
IV |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ CPL2012c; ADAS @ adas @ cpl2012d |
Serial |
2013 |
| Permanent link to this record |
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| Author |
Fernando Barrera; Felipe Lumbreras; Cristhian Aguilera; Angel Sappa |
| Title |
Planar-Based Multispectral Stereo |
Type |
Conference Article |
| Year |
2012 |
Publication |
11th Quantitative InfraRed Thermography |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
Naples, Italy |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
QIRT |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ BLA2012 |
Serial |
2016 |
| Permanent link to this record |
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| |
| Author |
Cristhian Aguilera; Fernando Barrera; Angel Sappa; Ricardo Toledo |
| Title |
A Novel SIFT-Like-Based Approach for FIR-VS Images Registration |
Type |
Conference Article |
| Year |
2012 |
Publication |
11th Quantitative InfraRed Thermography |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
Naples, Italy |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
QIRT |
| Notes |
ADAS; TV |
Approved |
no |
| Call Number |
Admin @ si @ ABS2012 |
Serial |
2017 |
| Permanent link to this record |
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| |
| Author |
Monica Piñol; Angel Sappa; Angeles Lopez; Ricardo Toledo |
| Title |
Feature Selection Based on Reinforcement Learning for Object Recognition |
Type |
Conference Article |
| Year |
2012 |
Publication |
Adaptive Learning Agents Workshop |
Abbreviated Journal |
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| Volume |
|
Issue |
|
Pages |
33-39 |
| Keywords |
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| Abstract |
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| Address |
Valencia |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
ALA |
| Notes |
ADAS; RV |
Approved |
no |
| Call Number |
Admin @ si @ PSL2012 |
Serial |
2018 |
| Permanent link to this record |
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| |
| Author |
German Ros; Angel Sappa; Daniel Ponsa; Antonio Lopez |
| Title |
Visual SLAM for Driverless Cars: A Brief Survey |
Type |
Conference Article |
| Year |
2012 |
Publication |
IEEE Workshop on Navigation, Perception, Accurate Positioning and Mapping for Intelligent Vehicles |
Abbreviated Journal |
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| Volume |
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Issue |
|
Pages |
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| Keywords |
SLAM |
| Abstract |
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| Address |
Alcalá de Henares |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
IVW |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ RSP2012; ADAS @ adas |
Serial |
2019 |
| Permanent link to this record |
| |
|
| |
| Author |
Naveen Onkarappa; Angel Sappa |
| Title |
An Empirical Study on Optical Flow Accuracy Depending on Vehicle Speed |
Type |
Conference Article |
| Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
1138-1143 |
| Keywords |
|
| Abstract |
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. |
| Address |
Alcalá de Henares |
| Corporate Author |
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Thesis |
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| Publisher |
IEEE Xplore |
Place of Publication |
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Editor |
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| Language |
|
Summary Language |
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Original Title |
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| Series Editor |
|
Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1931-0587 |
ISBN |
978-1-4673-2119-8 |
Medium |
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| Area |
|
Expedition |
|
Conference |
IV |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ NaS2012 |
Serial |
2020 |
| Permanent link to this record |
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| |
| Author |
Miguel Oliveira; Angel Sappa; V. Santos |
| Title |
Color Correction for Onboard Multi-camera Systems using 3D Gaussian Mixture Models |
Type |
Conference Article |
| Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
299-303 |
| Keywords |
|
| Abstract |
The current paper proposes a novel color correction approach for onboard multi-camera systems. It works by segmenting the given images into several regions. A probabilistic segmentation framework, using 3D Gaussian Mixture Models, is proposed. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. An image data set of road scenarios is used to establish a performance comparison of the proposed method with other seven well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches. |
| Address |
Alcalá de Henares |
| Corporate Author |
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Thesis |
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| Publisher |
IEEE Xplore |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1931-0587 |
ISBN |
978-1-4673-2119-8 |
Medium |
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| Area |
|
Expedition |
|
Conference |
IV |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ OSS2012b |
Serial |
2021 |
| Permanent link to this record |
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| |
| Author |
Naila Murray; Luca Marchesotti; Florent Perronnin |
| Title |
AVA: A Large-Scale Database for Aesthetic Visual Analysis |
Type |
Conference Article |
| Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
2408-2415 |
| Keywords |
|
| Abstract |
With the ever-expanding volume of visual content available, the ability to organize and navigate such content by aesthetic preference is becoming increasingly important. While still in its nascent stage, research into computational models of aesthetic preference already shows great potential. However, to advance research, realistic, diverse and challenging databases are needed. To this end, we introduce a new large-scale database for conducting Aesthetic Visual Analysis: AVA. It contains over 250,000 images along with a rich variety of meta-data including a large number of aesthetic scores for each image, semantic labels for over 60 categories as well as labels related to photographic style. We show the advantages of AVA with respect to existing databases in terms of scale, diversity, and heterogeneity of annotations. We then describe several key insights into aesthetic preference afforded by AVA. Finally, we demonstrate, through three applications, how the large scale of AVA can be leveraged to improve performance on existing preference tasks |
| Address |
Providence, Rhode Islan |
| Corporate Author |
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Thesis |
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| Publisher |
IEEE Xplore |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1063-6919 |
ISBN |
978-1-4673-1226-4 |
Medium |
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| Area |
|
Expedition |
|
Conference |
CVPR |
| Notes |
CIC |
Approved |
no |
| Call Number |
Admin @ si @ MMP2012a |
Serial |
2025 |
| Permanent link to this record |
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| |
| Author |
Marc Serra; Olivier Penacchio; Robert Benavente; Maria Vanrell |
| Title |
Names and Shades of Color for Intrinsic Image Estimation |
Type |
Conference Article |
| Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
278-285 |
| Keywords |
|
| Abstract |
In the last years, intrinsic image decomposition has gained attention. Most of the state-of-the-art methods are based on the assumption that reflectance changes come along with strong image edges. Recently, user intervention in the recovery problem has proved to be a remarkable source of improvement. In this paper, we propose a novel approach that aims to overcome the shortcomings of pure edge-based methods by introducing strong surface descriptors, such as the color-name descriptor which introduces high-level considerations resembling top-down intervention. We also use a second surface descriptor, termed color-shade, which allows us to include physical considerations derived from the image formation model capturing gradual color surface variations. Both color cues are combined by means of a Markov Random Field. The method is quantitatively tested on the MIT ground truth dataset using different error metrics, achieving state-of-the-art performance. |
| Address |
Providence, Rhode Island |
| Corporate Author |
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Thesis |
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| Publisher |
IEEE Xplore |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1063-6919 |
ISBN |
978-1-4673-1226-4 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
CVPR |
| Notes |
CIC |
Approved |
no |
| Call Number |
Admin @ si @ SPB2012 |
Serial |
2026 |
| Permanent link to this record |
| |
|
| |
| Author |
Naila Murray; Luca Marchesotti; Florent Perronnin |
| Title |
Learning to Rank Images using Semantic and Aesthetic Labels |
Type |
Conference Article |
| Year |
2012 |
Publication |
23rd British Machine Vision Conference |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
110.1-110.10 |
| Keywords |
|
| Abstract |
Most works on image retrieval from text queries have addressed the problem of retrieving semantically relevant images. However, the ability to assess the aesthetic quality of an image is an increasingly important differentiating factor for search engines. In this work, given a semantic query, we are interested in retrieving images which are semantically relevant and score highly in terms of aesthetics/visual quality. We use large-margin classifiers and rankers to learn statistical models capable of ordering images based on the aesthetic and semantic information. In particular, we compare two families of approaches: while the first one attempts to learn a single ranker which takes into account both semantic and aesthetic information, the second one learns separate semantic and aesthetic models. We carry out a quantitative and qualitative evaluation on a recently-published large-scale dataset and we show that the second family of techniques significantly outperforms the first one. |
| Address |
Guildford, London |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
1-901725-46-4 |
Medium |
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| Area |
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Expedition |
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Conference |
BMVC |
| Notes |
CIC |
Approved |
no |
| Call Number |
Admin @ si @ MMP2012b |
Serial |
2027 |
| Permanent link to this record |
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| Author |
Simeon Petkov; Adriana Romero; Xavier Carrillo; Petia Radeva; Carlo Gatta |
| Title |
Robust and accurate diaphragm border detection in cardiac X-Ray angiographies |
Type |
Conference Article |
| Year |
2012 |
Publication |
Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges |
Abbreviated Journal |
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| Volume |
7746 |
Issue |
|
Pages |
225-234 |
| Keywords |
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| Abstract |
Workshop STACOM, dins del MICCAI
X-ray angiography is the most common imaging modality employed in the diagnosis of coronary diseases prior to or during a catheter-based intervention. The analysis of the patient X-Ray sequence can provide useful information about the degree of arterial stenosis, the myocardial perfusion and other clinical parameters. If the sequence has been acquired to evaluate the perfusion grade, the opacity due to the diaphragm could potentially hinder any kind of visual inspection and make more difficult a computer aided measurements. In this paper we propose an accurate and robust method to automatically identify the diaphragm border in each frame. Quantitative evaluation on a set of 11 sequences shows that the proposed algorithm outperforms previous methods. |
| Address |
Nice, France |
| Corporate Author |
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Thesis |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-36960-5 |
Medium |
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| Area |
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Expedition |
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Conference |
STACOM |
| Notes |
MILAB |
Approved |
no |
| Call Number |
Admin @ si @ PRC2012 |
Serial |
2028 |
| Permanent link to this record |
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| |
| Author |
Murad Al Haj; Jordi Gonzalez; Larry S. Davis |
| Title |
On Partial Least Squares in Head Pose Estimation: How to simultaneously deal with misalignment |
Type |
Conference Article |
| Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
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| Volume |
|
Issue |
|
Pages |
2602-2609 |
| Keywords |
|
| Abstract |
Head pose estimation is a critical problem in many computer vision applications. These include human computer interaction, video surveillance, face and expression recognition. In most prior work on heads pose estimation, the positions of the faces on which the pose is to be estimated are specified manually. Therefore, the results are reported without studying the effect of misalignment. We propose a method based on partial least squares (PLS) regression to estimate pose and solve the alignment problem simultaneously. The contributions of this paper are two-fold: 1) we show that the kernel version of PLS (kPLS) achieves better than state-of-the-art results on the estimation problem and 2) we develop a technique to reduce misalignment based on the learned PLS factors. |
| Address |
Providence, Rhode Island |
| Corporate Author |
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Thesis |
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| Publisher |
IEEE Xplore |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1063-6919 |
ISBN |
978-1-4673-1226-4 |
Medium |
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| Area |
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Expedition |
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Conference |
CVPR |
| Notes |
ISE |
Approved |
no |
| Call Number |
Admin @ si @ HGD2012 |
Serial |
2029 |
| Permanent link to this record |
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| |
| Author |
Wenjuan Gong; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca |
| Title |
A New Image Dataset on Human Interactions |
Type |
Conference Article |
| Year |
2012 |
Publication |
7th Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
|
| Volume |
7378 |
Issue |
|
Pages |
204-209 |
| Keywords |
|
| Abstract |
This article describes a new collection of still image dataset which are dedicated to interactions between people. Human action recognition from still images have been a hot topic recently, but most of them are actions performed by a single person, like running, walking, riding bikes, phoning and so on and there is no interactions between people in one image. The dataset collected in this paper are concentrating on human interaction between two people aiming to explore this new topic in the research area of action recognition from still images. |
| Address |
Mallorca |
| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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| Language |
|
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-31566-4 |
Medium |
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| Area |
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Expedition |
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Conference |
AMDO |
| Notes |
ISE |
Approved |
no |
| Call Number |
Admin @ si @ GGT2012 |
Serial |
2030 |
| Permanent link to this record |
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| |
| Author |
German Ros; Jesus Martinez del Rincon; Gines Garcia-Mateos |
| Title |
Articulated Particle Filter for Hand Tracking |
Type |
Conference Article |
| Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
Abbreviated Journal |
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| Volume |
|
Issue |
|
Pages |
3581 - 3585 |
| Keywords |
|
| Abstract |
This paper proposes a new version of Particle Filter, called Articulated Particle Filter – ArPF -, which has been specifically designed for an efficient sampling of hierarchical spaces, generated by articulated objects. Our approach decomposes the articulated motion into layers for efficiency purposes, making use of a careful modeling of the diffusion noise along with its propagation through the articulations. This produces an increase of accuracy and prevent for divergences. The algorithm is tested on hand tracking due to its complex hierarchical articulated nature. With this purpose, a new dataset generation tool for quantitative evaluation is also presented in this paper. |
| Address |
Tsukuba Science City, Japan |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
|
| ISSN |
1051-4651 |
ISBN |
978-1-4673-2216-4 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
ICPR |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ RMG2012 |
Serial |
2031 |
| Permanent link to this record |
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| |
| Author |
Jose Carlos Rubio; Joan Serrat; Antonio Lopez |
| Title |
Unsupervised co-segmentation through region matching |
Type |
Conference Article |
| Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
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| Volume |
|
Issue |
|
Pages |
749-756 |
| Keywords |
|
| Abstract |
Co-segmentation is defined as jointly partitioning multiple images depicting the same or similar object, into foreground and background. Our method consists of a multiple-scale multiple-image generative model, which jointly estimates the foreground and background appearance distributions from several images, in a non-supervised manner. In contrast to other co-segmentation methods, our approach does not require the images to have similar foregrounds and different backgrounds to function properly. Region matching is applied to exploit inter-image information by establishing correspondences between the common objects that appear in the scene. Moreover, computing many-to-many associations of regions allow further applications, like recognition of object parts across images. We report results on iCoseg, a challenging dataset that presents extreme variability in camera viewpoint, illumination and object deformations and poses. We also show that our method is robust against large intra-class variability in the MSRC database. |
| Address |
Providence, Rhode Island |
| Corporate Author |
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Thesis |
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| Publisher |
IEEE Xplore |
Place of Publication |
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Editor |
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| Language |
|
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1063-6919 |
ISBN |
978-1-4673-1226-4 |
Medium |
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| Area |
|
Expedition |
|
Conference |
CVPR |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ RSL2012b; ADAS @ adas @ |
Serial |
2033 |
| Permanent link to this record |
