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Author |
Jose Carlos Rubio |
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Title |
Graph matching based on graphical models with application to vehicle tracking and classification at night |
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2009 |
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CVC Technical Report |
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144 |
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Computer Vision Center |
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Master's thesis |
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Bellaterra, Barcelona |
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CIC |
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no |
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Admin @ si @ Rub2009 |
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2398 |
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Author |
Farshad Nourbakhsh |
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Title |
Colour logo recognition |
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2009 |
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CVC Technical Report |
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145 |
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Computer Vision Center |
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Master's thesis |
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Bellaterra, Barcelona |
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DAG |
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no |
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Admin @ si @ Nou2009 |
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2399 |
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Author |
Enric Sala |
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Title |
Off-line person-dependent signature verification |
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2009 |
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CVC Technical Report |
Abbreviated Journal |
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146 |
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Computer Vision Center |
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Master's thesis |
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Bellaterra, Barcelona |
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no |
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Admin @ si @ Sal2009 |
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2400 |
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Author |
Wenjuan Gong |
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Title |
Action priors for human pose tracking by particle filter |
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2009 |
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CVC Technical Report |
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Computer Vision Center |
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Master's thesis |
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Bellaterra, Barcelona |
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ISE |
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no |
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Call Number |
Admin @ si @ Gon2009 |
Serial |
2401 |
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Author |
Diego Alejandro Cheda |
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Title |
Monocular egomotion estimation for ADAS application |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
148 |
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Corporate Author |
Computer Vision Center |
Thesis |
Ph.D. thesis |
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Place of Publication |
Bellaterra, Barcelona |
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ADAS |
Approved |
no |
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Call Number |
Admin @ si @ Che2009 |
Serial |
2402 |
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Author |
Javier Marin |
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Title |
Virtual learning for real testing |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
150 |
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Computer Vision Center |
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Master's thesis |
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Place of Publication |
bell |
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ADAS |
Approved |
no |
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Call Number |
Admin @ si @ Mar2009c |
Serial |
2403 |
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Author |
Ivet Rafegas |
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Title |
Exploring Low-Level Vision Models. Case Study: Saliency Prediction |
Type |
Report |
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Year |
2013 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
175 |
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Master's thesis |
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CIC |
Approved |
no |
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Call Number |
Admin @ si @ Raf2013 |
Serial |
2409 |
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Author |
Francesco Brughi |
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Title |
Artistic Heritage Motive Retrieval: an Explorative Study |
Type |
Report |
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Year |
2013 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
176 |
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Master's thesis |
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Notes |
IAM |
Approved |
no |
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Call Number |
Admin @ si @ Bru2013 |
Serial |
2410 |
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Author |
Bhaskar Chakraborty; Jordi Gonzalez; Xavier Roca |
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Title |
Large scale continuous visual event recognition using max-margin Hough transformation framework |
Type |
Journal Article |
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Year |
2013 |
Publication |
Computer Vision and Image Understanding |
Abbreviated Journal |
CVIU |
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Volume |
117 |
Issue |
10 |
Pages |
1356–1368 |
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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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ISE |
Approved |
no |
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Call Number |
Admin @ si @ CGR2013 |
Serial |
2413 |
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Author |
German Ros |
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Title |
Visual SLAM for Driverless Cars: An Initial Survey |
Type |
Report |
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Year |
2012 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
170 |
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Master's thesis |
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ADAS |
Approved |
no |
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Call Number |
Admin @ si @ Ros2012c |
Serial |
2414 |
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Author |
Xu Hu |
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Title |
Real-Time Part Based Models for Object Detection |
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Report |
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2012 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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171 |
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Master's thesis |
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ADAS;ISE |
Approved |
no |
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Call Number |
Admin @ si @ Hu2012 |
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2415 |
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Author |
Nuria Cirera |
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Title |
Recognition of Handwritten Historical Documents |
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Report |
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Year |
2012 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
174 |
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Master's thesis |
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DAG |
Approved |
no |
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Call Number |
Admin @ si @ Cir2012 |
Serial |
2416 |
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Author |
Adria Ruiz; Joost Van de Weijer; Xavier Binefa |
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Title |
Regularized Multi-Concept MIL for weakly-supervised facial behavior categorization |
Type |
Conference Article |
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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. |
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Nottingham; UK; September 2014 |
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BMVC |
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Notes |
LAMP; CIC; 600.074; 600.079 |
Approved |
no |
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Call Number |
Admin @ si @ RWB2014 |
Serial |
2508 |
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Author |
Ferran Poveda |
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Title |
Computer Graphics and Vision Techniques for the Study of the Muscular Fiber Architecture of the Myocardium |
Type |
Book Whole |
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Year |
2013 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Thesis |
Ph.D. thesis |
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Editor |
Debora Gil;Enric Marti |
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IAM |
Approved |
no |
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Call Number |
Admin @ si @ Pov2013 |
Serial |
2417 |
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Author |
T.Chauhan; E.Perales; Kaida Xiao; E.Hird ; Dimosthenis Karatzas; Sophie Wuerger |
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Title |
The achromatic locus: Effect of navigation direction in color space |
Type |
Journal Article |
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Year |
2014 |
Publication |
Journal of Vision |
Abbreviated Journal |
VSS |
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Volume |
14 (1) |
Issue |
25 |
Pages |
1-11 |
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Keywords |
achromatic; unique hues; color constancy; luminance; color space |
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Abstract |
5Y Impact Factor: 2.99 / 1st (Ophthalmology)
An achromatic stimulus is defined as a patch of light that is devoid of any hue. This is usually achieved by asking observers to adjust the stimulus such that it looks neither red nor green and at the same time neither yellow nor blue. Despite the theoretical and practical importance of the achromatic locus, little is known about the variability in these settings. The main purpose of the current study was to evaluate whether achromatic settings were dependent on the task of the observers, namely the navigation direction in color space. Observers could either adjust the test patch along the two chromatic axes in the CIE u*v* diagram or, alternatively, navigate along the unique-hue lines. Our main result is that the navigation method affects the reliability of these achromatic settings. Observers are able to make more reliable achromatic settings when adjusting the test patch along the directions defined by the four unique hues as opposed to navigating along the main axes in the commonly used CIE u*v* chromaticity plane. This result holds across different ambient viewing conditions (Dark, Daylight, Cool White Fluorescent) and different test luminance levels (5, 20, and 50 cd/m2). The reduced variability in the achromatic settings is consistent with the idea that internal color representations are more aligned with the unique-hue lines than the u* and v* axes. |
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DAG; 600.077 |
Approved |
no |
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Call Number |
Admin @ si @ CPX2014 |
Serial |
2418 |
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| Permanent link to this record |
