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| Author | M. Bressan; David Guillamet; Jordi Vitria | ||||
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Using an ICA Representation of Local Color Histograms for Object Recognition | Type | Journal | ||
| Year | 2003 | Publication | Pattern Recognition, 36(3):691–701 (IF: 1.611) | Abbreviated Journal | |
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| Notes | OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ BGV2003 | Serial | 365 | ||
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| Author | M. Bressan; David Guillamet; Jordi Vitria | ||||
| Title |
Using a local ICA Representation of High Dimensional Data for Object Recognition and Classification. | Type | Miscellaneous | ||
| Year | 2001 | Publication | Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR). | Abbreviated Journal | |
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| Address | Hawaii | ||||
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| Notes | OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ BGV2001 | Serial | 75 | ||
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| Author | Pierluigi Casale; Oriol Pujol; Petia Radeva | ||||
| Title |
User Verification From Walking Activity. First Steps Towards a Personal Verification System | Type | Conference Article | ||
| Year | 2011 | Publication | 1st International Conference on Pervasive and Embedded Computing and Communication Systems | Abbreviated Journal | |
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| Address | Algarve, Portugal | ||||
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| Area | Expedition | Conference | PECCS | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ CPR2011c | Serial | 1762 | ||
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| Author | Albert Clapes; Miguel Reyes; Sergio Escalera | ||||
| Title |
User Identification and Object Recognition in Clutter Scenes Based on RGB-Depth Analysis | Type | Conference Article | ||
| Year | 2012 | Publication | 7th Conference on Articulated Motion and Deformable Objects | Abbreviated Journal | |
| Volume | 7378 | Issue | Pages | 1-11 | |
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| Abstract | We propose an automatic system for user identification and object recognition based on multi-modal RGB-Depth data analysis. We model a RGBD environment learning a pixel-based background Gaussian distribution. Then, user and object candidate regions are detected and recognized online using robust statistical approaches over RGBD descriptions. Finally, the system saves the historic of user-object assignments, being specially useful for surveillance scenarios. The system has been evaluated on a novel data set containing different indoor/outdoor scenarios, objects, and users, showing accurate recognition and better performance than standard state-of-the-art approaches. | ||||
| Address | Mallorca | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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| ISSN | 0302-9743 | ISBN | 978-3-642-31566-4 | Medium | |
| Area | Expedition | Conference | AMDO | ||
| Notes | HUPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ CRE2012 | Serial | 2010 | ||
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| Author | Maya Dimitrova; N. Kushmerick; Petia Radeva; Juan J. Villanueva | ||||
| Title |
User Assesment of a Visual Genre Classifier | Type | Miscellaneous | ||
| Year | 2003 | Publication | Proceedings of the 3rd IASTED Int. Conference Visualization, Imaging and Image Processing | Abbreviated Journal | |
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| Notes | MILAB | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ DKR2003 | Serial | 372 | ||
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| Author | F. Javier Sanchez; Jorge Bernal | ||||
| Title |
Use of Software Tools for Real-time Monitoring of Learning Processes: Application to Compilers subject | Type | Conference Article | ||
| Year | 2018 | Publication | 4th International Conference of Higher Education Advances | Abbreviated Journal | |
| Volume | Issue | Pages | 1359-1366 | ||
| Keywords | Monitoring; Evaluation tool; Gamification; Student motivation | ||||
| Abstract | The effective implementation of the Higher European Education Area has meant a change regarding the focus of the learning process, being now the student at its very center. This shift of focus requires a strong involvement and fluent communication between teachers and students to succeed. Considering the difficulties associated to motivate students to take a more active role in the learning process, we explore how the use of a software tool can help both actors to improve the learning experience. We present a tool that can help students to obtain instantaneous feedback with respect to their progress in the subject as well as providing teachers with useful information about the evolution of knowledge acquisition with respect to each of the subject areas. We compare the performance achieved by students in two academic years: results show an improvement in overall performance which, after observing graphs provided by our tool, can be associated to an increase in students interest in the subject. | ||||
| Address | Valencia; June 2018 | ||||
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| Area | Expedition | Conference | HEAD | ||
| Notes | MV; no proj | Approved | no | ||
| Call Number | Admin @ si @ SaB2018 | Serial | 3165 | ||
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| Author | Jorge Bernal | ||||
| Title |
Use of Projection and Back-projection Methods in Bidimensional Computed Tomography Image Reconstruction | Type | Report | ||
| Year | 2009 | Publication | CVC Tecnical Report | Abbreviated Journal | |
| Volume | 141 | Issue | Pages | ||
| Keywords | Projection, Back-projection, CT scan, Euclidean geometry, Radon transform | ||||
| Abstract | One of the biggest drawbacks related to the use of CT scanners is the cost (in memory and in time) associated. In this project many methods to simulate their functioning, but in a more feasible way (taking an industrial point of view), will be studied.
The main group of techniques that are being used are the one entitled as ’back-projection’. The concept behind is to simulate the X ray emission in CT scans by lines that cross with the image we want to reconstruct. In the first part of this document euclidean geometry is used to face the tasks of projec- tion and back-projection. After analysing the results achieved it has been proved that this approach does not lead to a fully perfect reconstruction (and also has some other problems related to running time and memory cost). Because of this in the second part of the document ’Filtered Back-projection’ method is introduced in order to improve the results. Filtered Back-projection methods rely on mathematical transforms (Fourier, Radon) in order to provide more accurate results that can be obtained in much less time. The main cause of this better results is the use of a filtering process before the back-projection in order to avoid high frequency-caused errors. As a result of this project two different implementations (one for each approach) had been implemented in order to compare their performance. |
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| Corporate Author | Computer Vision Center | Thesis | Master's thesis | ||
| Publisher | Place of Publication | Barcelona, Spain | Editor | ||
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| Area | 800 | Expedition | Conference | ||
| Notes | MV; | Approved | no | ||
| Call Number | IAM @ iam @ Ber2009 | Serial | 1693 | ||
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| Author | Lluis Pere de las Heras; Oriol Ramos Terrades; Josep Llados; David Fernandez; Cristina Cañero | ||||
| Title |
Use case visual Bag-of-Words techniques for camera based identity document classification | Type | Conference Article | ||
| Year | 2015 | Publication | 13th International Conference on Document Analysis and Recognition ICDAR2015 | Abbreviated Journal | |
| Volume | Issue | Pages | 721 - 725 | ||
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| Abstract | Nowadays, automatic identity document recognition, including passport and driving license recognition, is at the core of many applications within the administrative and service sectors, such as police, hospitality, car renting, etc. In former years, the document information was manually extracted whereas today this data is recognized automatically from images obtained by flat-bed scanners. Yet, since these scanners tend to be expensive and voluminous, companies in the sector have recently turned their attention to cheaper, small and yet computationally powerful scanners: the mobile devices. The document identity recognition from mobile images enclose several new difficulties w.r.t traditional scanned images, such as the loss of a controlled background, perspective, blurring, etc. In this paper we present a real application for identity document classification of images taken from mobile devices. This classification process is of extreme importance since a prior knowledge of the document type and origin strongly facilitates the subsequent information extraction. The proposed method is based on a traditional Bagof-Words in which we have taken into consideration several key aspects to enhance recognition rate. The method performance has been studied on three datasets containing more than 2000 images from 129 different document classes. | ||||
| Address | Nancy; France; August 2015 | ||||
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| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.077; 600.061; | Approved | no | ||
| Call Number | Admin @ si @ HRL2015a | Serial | 2726 | ||
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| Author | Aniol Lidon; Xavier Giro; Marc Bolaños; Petia Radeva; Markus Seidl; Matthias Zeppelzauer | ||||
| Title |
UPC-UB-STP @ MediaEval 2015 diversity task: iterative reranking of relevant images | Type | Conference Article | ||
| Year | 2015 | Publication | 2015 MediaEval Retrieving Diverse Images Task | Abbreviated Journal | |
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| Abstract | This paper presents the results of the UPC-UB-STP team in the 2015 MediaEval Retrieving Diverse Images Task. The goal of the challenge is to provide a ranked list of Flickr photos for a predefined set of queries. Our approach firstly generates a ranking of images based on a query-independent estimation of its relevance. Only top results are kept and iteratively re-ranked based on their intra-similarity to introduce diversity. | ||||
| Address | Wurzen; Germany; September 2015 | ||||
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| Area | Expedition | Conference | MediaEval | ||
| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @LGB2016 | Serial | 2793 | ||
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| Author | Mickael Cormier; Andreas Specker; Julio C. S. Jacques; Lucas Florin; Jurgen Metzler; Thomas B. Moeslund; Kamal Nasrollahi; Sergio Escalera; Jurgen Beyerer | ||||
| Title |
UPAR Challenge: Pedestrian Attribute Recognition and Attribute-based Person Retrieval – Dataset, Design, and Results | Type | Conference Article | ||
| Year | 2023 | Publication | 2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops | Abbreviated Journal | |
| Volume | Issue | Pages | 166-175 | ||
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| Abstract | In civilian video security monitoring, retrieving and tracking a person of interest often rely on witness testimony and their appearance description. Deployed systems rely on a large amount of annotated training data and are expected to show consistent performance in diverse areas and gen-eralize well between diverse settings w.r.t. different view-points, illumination, resolution, occlusions, and poses for indoor and outdoor scenes. However, for such generalization, the system would require a large amount of various an-notated data for training and evaluation. The WACV 2023 Pedestrian Attribute Recognition and Attributed-based Per-son Retrieval Challenge (UPAR-Challenge) aimed to spot-light the problem of domain gaps in a real-world surveil-lance context and highlight the challenges and limitations of existing methods. The UPAR dataset, composed of 40 important binary attributes over 12 attribute categories across four datasets, was extended with data captured from a low-flying UAV from the P-DESTRE dataset. To this aim, 0.6M additional annotations were manually labeled and vali-dated. Each track evaluated the robustness of the competing methods to domain shifts by training on limited data from a specific domain and evaluating using data from unseen do-mains. The challenge attracted 41 registered participants, but only one team managed to outperform the baseline on one track, emphasizing the task's difficulty. This work de-scribes the challenge design, the adopted dataset, obtained results, as well as future directions on the topic. | ||||
| Address | Waikoloa; Hawai; USA; January 2023 | ||||
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| Area | Expedition | Conference | WACVW | ||
| Notes | HUPBA | Approved | no | ||
| Call Number | Admin @ si @ CSJ2023 | Serial | 3902 | ||
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| Author | Fernando Vilariño | ||||
| Title |
Unveiling the Social Impact of AI | Type | Conference Article | ||
| Year | 2020 | Publication | Workshop at Digital Living Lab Days Conference | Abbreviated Journal | |
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| Address | September 2020 | ||||
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| Notes | MV; DAG; 600.121; 600.140;SIAI | Approved | no | ||
| Call Number | Admin @ si @ Vil2020 | Serial | 3459 | ||
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| Author | Mohamed Ramzy Ibrahim; Robert Benavente; Daniel Ponsa; Felipe Lumbreras | ||||
| Title |
Unveiling the Influence of Image Super-Resolution on Aerial Scene Classification | Type | Conference Article | ||
| Year | 2023 | Publication | Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications | Abbreviated Journal | |
| Volume | 14469 | Issue | Pages | 214–228 | |
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| Abstract | Deep learning has made significant advances in recent years, and as a result, it is now in a stage where it can achieve outstanding results in tasks requiring visual understanding of scenes. However, its performance tends to decline when dealing with low-quality images. The advent of super-resolution (SR) techniques has started to have an impact on the field of remote sensing by enabling the restoration of fine details and enhancing image quality, which could help to increase performance in other vision tasks. However, in previous works, contradictory results for scene visual understanding were achieved when SR techniques were applied. In this paper, we present an experimental study on the impact of SR on enhancing aerial scene classification. Through the analysis of different state-of-the-art SR algorithms, including traditional methods and deep learning-based approaches, we unveil the transformative potential of SR in overcoming the limitations of low-resolution (LR) aerial imagery. By enhancing spatial resolution, more fine details are captured, opening the door for an improvement in scene understanding. We also discuss the effect of different image scales on the quality of SR and its effect on aerial scene classification. Our experimental work demonstrates the significant impact of SR on enhancing aerial scene classification compared to LR images, opening new avenues for improved remote sensing applications. | ||||
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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| Area | Expedition | Conference | CIARP | ||
| Notes | MSIAU | Approved | no | ||
| Call Number | Admin @ si @ IBP2023 | Serial | 4008 | ||
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| Author | Jose Antonio Rodriguez; Florent Perronnin; Gemma Sanchez; Josep Llados | ||||
| Title |
Unsupervised writer style adaptation for handwritten word spotting | Type | Conference Article | ||
| Year | 2008 | Publication | Pattern Recognition. 19th International Conference on, IBM Best Student Paper Award. | Abbreviated Journal | |
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| Address | Tampa, USA | ||||
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| Area | Expedition | Conference | ICPR | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ RPS2008 | Serial | 1077 | ||
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| Author | Jose Antonio Rodriguez; Florent Perronnin; Gemma Sanchez; Josep Llados | ||||
| Title |
Unsupervised writer adaptation of whole-word HMMs with application to word-spotting | Type | Journal Article | ||
| Year | 2010 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 31 | Issue | 8 | Pages | 742–749 |
| Keywords | Word-spotting; Handwriting recognition; Writer adaptation; Hidden Markov model; Document analysis | ||||
| Abstract | In this paper we propose a novel approach for writer adaptation in a handwritten word-spotting task. The method exploits the fact that the semi-continuous hidden Markov model separates the word model parameters into (i) a codebook of shapes and (ii) a set of word-specific parameters.
Our main contribution is to employ this property to derive writer-specific word models by statistically adapting an initial universal codebook to each document. This process is unsupervised and does not even require the appearance of the keyword(s) in the searched document. Experimental results show an increase in performance when this adaptation technique is applied. To the best of our knowledge, this is the first work dealing with adaptation for word-spotting. The preliminary version of this paper obtained an IBM Best Student Paper Award at the 19th International Conference on Pattern Recognition. |
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| Publisher | Elsevier | Place of Publication | Editor | ||
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| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ RPS2010 | Serial | 1290 | ||
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| Author | Lluis Pere de las Heras; David Fernandez; Ernest Valveny; Josep Llados; Gemma Sanchez | ||||
| Title |
Unsupervised wall detector in architectural floor plan | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 1245-1249 | ||
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| Abstract | Wall detection in floor plans is a crucial step in a complete floor plan recognition system. Walls define the main structure of buildings and convey essential information for the detection of other structural elements. Nevertheless, wall segmentation is a difficult task, mainly because of the lack of a standard graphical notation. The existing approaches are restricted to small group of similar notations or require the existence of pre-annotated corpus of input images to learn each new notation. In this paper we present an automatic wall segmentation system, with the ability to handle completely different notations without the need of any annotated dataset. It only takes advantage of the general knowledge that walls are a repetitive element, naturally distributed within the plan and commonly modeled by straight parallel lines. The method has been tested on four datasets of real floor plans with different notations, and compared with the state-of-the-art. The results show its suitability for different graphical notations, achieving higher recall rates than the rest of the methods while keeping a high average precision. | ||||
| Address | Washington; USA; August 2013 | ||||
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| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.061; 600.056; 600.045 | Approved | no | ||
| Call Number | Admin @ si @ HFV2013 | Serial | 2319 | ||
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