| Records |
| Author |
Shida Beigpour |
| Title |
Physics-based Reflectance Estimation Applied to Recoloring |
Type |
Report |
| Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
137 |
Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
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| Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
Publisher  |
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Place of Publication |
Bellaterra, Barcelona |
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CIC |
Approved |
no |
| Call Number |
Admin @ si @ Bei2009 |
Serial |
2396 |
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| Author |
Jaume Gibert |
| Title |
Learning structural representations and graph matching paradigms in the context of object recognition |
Type |
Report |
| Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
143 |
Issue |
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Pages |
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| Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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DAG |
Approved |
no |
| Call Number |
Admin @ si @ Gib2009 |
Serial |
2397 |
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| Author |
Jose Carlos Rubio |
| Title |
Graph matching based on graphical models with application to vehicle tracking and classification at night |
Type |
Report |
| Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
144 |
Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
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| Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
| Publisher |
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Place of Publication |
Bellaterra, Barcelona |
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| Notes |
CIC |
Approved |
no |
| Call Number |
Admin @ si @ Rub2009 |
Serial |
2398 |
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| Author |
Farshad Nourbakhsh |
| Title |
Colour logo recognition |
Type |
Report |
| Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
145 |
Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
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| Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
| Publisher |
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Place of Publication |
Bellaterra, Barcelona |
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DAG |
Approved |
no |
| Call Number |
Admin @ si @ Nou2009 |
Serial |
2399 |
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| Author |
Enric Sala |
| Title |
Off-line person-dependent signature verification |
Type |
Report |
| Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
146 |
Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
| Publisher |
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Place of Publication |
Bellaterra, Barcelona |
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Approved |
no |
| Call Number |
Admin @ si @ Sal2009 |
Serial |
2400 |
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| Author |
Wenjuan Gong |
| Title |
Action priors for human pose tracking by particle filter |
Type |
Report |
| Year |
2009 |
Publication |
CVC Technical Report |
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 |
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| Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
| Publisher |
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Place of Publication |
Bellaterra, Barcelona |
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| Notes |
ISE |
Approved |
no |
| Call Number |
Admin @ si @ Gon2009 |
Serial |
2401 |
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| Author |
Diego Alejandro Cheda |
| Title |
Monocular egomotion estimation for ADAS application |
Type |
Report |
| Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
148 |
Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Corporate Author |
Computer Vision Center |
Thesis |
Ph.D. thesis |
| Publisher |
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Place of Publication |
Bellaterra, Barcelona |
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| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ Che2009 |
Serial |
2402 |
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| Author |
Javier Marin |
| Title |
Virtual learning for real testing |
Type |
Report |
| Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
150 |
Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
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| Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
| Publisher |
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Place of Publication |
bell |
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ADAS |
Approved |
no |
| Call Number |
Admin @ si @ Mar2009c |
Serial |
2403 |
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| Author |
Ivet Rafegas |
| Title |
Exploring Low-Level Vision Models. Case Study: Saliency Prediction |
Type |
Report |
| Year |
2013 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
175 |
Issue |
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Pages |
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Thesis |
Master's thesis |
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CIC |
Approved |
no |
| Call Number |
Admin @ si @ Raf2013 |
Serial |
2409 |
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| Author |
Francesco Brughi |
| Title |
Artistic Heritage Motive Retrieval: an Explorative Study |
Type |
Report |
| Year |
2013 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
176 |
Issue |
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Pages |
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Thesis |
Master's thesis |
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| Notes |
IAM |
Approved |
no |
| Call Number |
Admin @ si @ Bru2013 |
Serial |
2410 |
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| Author |
Bhaskar Chakraborty; Jordi Gonzalez; Xavier Roca |
| Title |
Large scale continuous visual event recognition using max-margin Hough transformation framework |
Type |
Journal Article |
| Year |
2013 |
Publication |
Computer Vision and Image Understanding |
Abbreviated Journal |
CVIU |
| Volume |
117 |
Issue |
10 |
Pages |
1356–1368 |
| Keywords |
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| Abstract |
In this paper we propose a novel method for continuous visual event recognition (CVER) on a large scale video dataset using max-margin Hough transformation framework. Due to high scalability, diverse real environmental state and wide scene variability direct application of action recognition/detection methods such as spatio-temporal interest point (STIP)-local feature based technique, on the whole dataset is practically infeasible. To address this problem, we apply a motion region extraction technique which is based on motion segmentation and region clustering to identify possible candidate “event of interest” as a preprocessing step. On these candidate regions a STIP detector is applied and local motion features are computed. For activity representation we use generalized Hough transform framework where each feature point casts a weighted vote for possible activity class centre. A max-margin frame work is applied to learn the feature codebook weight. For activity detection, peaks in the Hough voting space are taken into account and initial event hypothesis is generated using the spatio-temporal information of the participating STIPs. For event recognition a verification Support Vector Machine is used. An extensive evaluation on benchmark large scale video surveillance dataset (VIRAT) and as well on a small scale benchmark dataset (MSR) shows that the proposed method is applicable on a wide range of continuous visual event recognition applications having extremely challenging conditions. |
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| ISSN |
1077-3142 |
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| Notes |
ISE |
Approved |
no |
| Call Number |
Admin @ si @ CGR2013 |
Serial |
2413 |
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| Author |
German Ros |
| Title |
Visual SLAM for Driverless Cars: An Initial Survey |
Type |
Report |
| Year |
2012 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
170 |
Issue |
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Pages |
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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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Thesis |
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 |
A. Ruiz; Joost Van de Weijer; Xavier Binefa |
| Title |
Regularized Multi-Concept MIL for weakly-supervised facial behavior categorization |
Type |
Conference Article |
| Year |
2014 |
Publication |
25th British Machine Vision Conference |
Abbreviated Journal |
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| Abstract |
We address the problem of estimating high-level semantic labels for videos of recorded people by means of analysing their facial expressions. This problem, to which we refer as facial behavior categorization, is a weakly-supervised learning problem where we do not have access to frame-by-frame facial gesture annotations but only weak-labels at the video level are available. Therefore, the goal is to learn a set of discriminative expressions and how they determine the video weak-labels. Facial behavior categorization can be posed as a Multi-Instance-Learning (MIL) problem and we propose a novel MIL method called Regularized Multi-Concept MIL to solve it. In contrast to previous approaches applied in facial behavior analysis, RMC-MIL follows a Multi-Concept assumption which allows different facial expressions (concepts) to contribute differently to the video-label. Moreover, to handle with the high-dimensional nature of facial-descriptors, RMC-MIL uses a discriminative approach to model the concepts and structured sparsity regularization to discard non-informative features. RMC-MIL is posed as a convex-constrained optimization problem where all the parameters are jointly learned using the Projected-Quasi-Newton method. In our experiments, we use two public data-sets to show the advantages of the Regularized Multi-Concept approach and its improvement compared to existing MIL methods. RMC-MIL outperforms state-of-the-art results in the UNBC data-set for pain detection. |
| Address |
Nottingham; UK; September 2014 |
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BMVC |
| Notes |
LAMP; CIC; 600.074; 600.079 |
Approved |
no |
| Call Number |
Admin @ si @ RWB2014 |
Serial |
2508 |
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