| Records |
| Author |
Albert Ali Salah; Theo Gevers; Nicu Sebe; Alessandro Vinciarelli |
| Title |
Computer Vision for Ambient Intelligence |
Type |
Journal Article |
| Year |
2011 |
Publication |
Journal of Ambient Intelligence and Smart Environments |
Abbreviated Journal |
JAISE |
| Volume |
3 |
Issue |
3 |
Pages |
187-191 |
| Keywords |
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| Abstract |
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Place of Publication |
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Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title  |
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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 |
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| Notes |
ISE |
Approved |
no |
| Call Number |
Admin @ si @ SGS2011a |
Serial |
1725 |
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| Author |
Arnau Ramisa; Alex Goldhoorn; David Aldavert; Ricardo Toledo; Ramon Lopez de Mantaras |
| Title |
Combining Invariant Features and the ALV Homing Method for Autonomous Robot Navigation Based on Panoramas |
Type |
Journal Article |
| Year |
2011 |
Publication |
Journal of Intelligent and Robotic Systems |
Abbreviated Journal |
JIRC |
| Volume |
64 |
Issue |
3-4 |
Pages |
625-649 |
| Keywords |
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| Abstract |
Biologically inspired homing methods, such as the Average Landmark Vector, are an interesting solution for local navigation due to its simplicity. However, usually they require a modification of the environment by placing artificial landmarks in order to work reliably. In this paper we combine the Average Landmark Vector with invariant feature points automatically detected in panoramic images to overcome this limitation. The proposed approach has been evaluated first in simulation and, as promising results are found, also in two data sets of panoramas from real world environments. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Netherlands |
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 |
0921-0296 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
RV;ADAS |
Approved |
no |
| Call Number |
Admin @ si @ RGA2011 |
Serial |
1728 |
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| Author |
Koen E.A. van de Sande; Theo Gevers; Cees G.M. Snoek |
| Title |
Empowering Visual Categorization with the GPU |
Type |
Journal Article |
| Year |
2011 |
Publication |
IEEE Transactions on Multimedia |
Abbreviated Journal |
TMM |
| Volume |
13 |
Issue |
1 |
Pages |
60-70 |
| Keywords |
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| Abstract |
Visual categorization is important to manage large collections of digital images and video, where textual meta-data is often incomplete or simply unavailable. The bag-of-words model has become the most powerful method for visual categorization of images and video. Despite its high accuracy, a severe drawback of this model is its high computational cost. As the trend to increase computational power in newer CPU and GPU architectures is to increase their level of parallelism, exploiting this parallelism becomes an important direction to handle the computational cost of the bag-of-words approach. When optimizing a system based on the bag-of-words approach, the goal is to minimize the time it takes to process batches of images. Additionally, we also consider power usage as an evaluation metric. In this paper, we analyze the bag-of-words model for visual categorization in terms of computational cost and identify two major bottlenecks: the quantization step and the classification step. We address these two bottlenecks by proposing two efficient algorithms for quantization and classification by exploiting the GPU hardware and the CUDA parallel programming model. The algorithms are designed to (1) keep categorization accuracy intact, (2) decompose the problem and (3) give the same numerical results. In the experiments on large scale datasets it is shown that, by using a parallel implementation on the Geforce GTX260 GPU, classifying unseen images is 4.8 times faster than a quad-core CPU version on the Core i7 920, while giving the exact same numerical results. In addition, we show how the algorithms can be generalized to other applications, such as text retrieval and video retrieval. Moreover, when the obtained speedup is used to process extra video frames in a video retrieval benchmark, the accuracy of visual categorization is improved by 29%. |
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Place of Publication |
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Medium |
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Expedition |
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Conference |
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| Notes |
ISE |
Approved |
no |
| Call Number |
Admin @ si @ SGS2011b |
Serial |
1729 |
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| Author |
Jordi Vitria; Joao Sanchez; Miguel Raposo; Mario Hernandez |
| Title |
Pattern Recognition and Image Analysis |
Type |
Book Whole |
| Year |
2011 |
Publication |
5th Iberian Conference Pattern Recognition and Image Analysis |
Abbreviated Journal |
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| Volume |
6669 |
Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
Las Palmas de Gran Canaria. Spain |
| Corporate Author |
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Thesis |
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| Publisher |
Springer-Verlag |
Place of Publication |
Berlin |
Editor |
J. Vitrià; J. Sanchez; M. Raposo; M. Hernandez |
| 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 |
978-3-642-2125 |
Medium |
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| Area |
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Expedition |
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Conference |
IbPRIA |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
Admin @ si @ VSR2011 |
Serial |
1730 |
| Permanent link to this record |
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| Author |
Mario Rojas; David Masip; Jordi Vitria |
| Title |
Automatic Detection of Facial Feature Points via HOGs and Geometric Prior Models |
Type |
Conference Article |
| Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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| Volume |
6669 |
Issue |
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Pages |
371-378 |
| Keywords |
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| Abstract |
Most applications dealing with problems involving the face require a robust estimation of the facial salient points. Nevertheless, this estimation is not usually an automated preprocessing step in applications dealing with facial expression recognition. In this paper we present a simple method to detect facial salient points in the face. It is based on a prior Point Distribution Model and a robust object descriptor. The model learns the distribution of the points from the training data, as well as the amount of variation in location each point exhibits. Using this model, we reduce the search areas to look for each point. In addition, we also exploit the global consistency of the points constellation, increasing the detection accuracy. The method was tested on two separate data sets and the results, in some cases, outperform the state of the art. |
| Address |
Las Palmas de Gran Canaria. Spain |
| 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 |
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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 |
0302-9743 |
ISBN |
978-3-642-21256-7 |
Medium |
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| Area |
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Expedition |
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Conference |
IbPRIA |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
Admin @ si @ RMV2011a |
Serial |
1731 |
| Permanent link to this record |
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| Author |
Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria; Petia Radeva |
| Title |
Interactive Labeling of WCE Images |
Type |
Conference Article |
| Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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| Volume |
6669 |
Issue |
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Pages |
143-150 |
| Keywords |
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| Abstract |
A high quality labeled training set is necessary for any supervised machine learning algorithm. Labeling of the data can be a very expensive process, specially while dealing with data of high variability and complexity. A good example of such data are the videos from Wireless Capsule Endoscopy. Building a representative WCE data set means many videos to be labeled by an expert. The problem that occurs is the data diversity, in the space of the features, from different WCE studies. That means that when new data arrives it is highly probable that it will not be represented in the training set, thus getting a high probability of performing an error when applying machine learning schemes. In this paper an interactive labeling scheme that allows reducing expert effort in the labeling process is presented. It is shown that the number of human interventions can be significantly reduced. The proposed system allows the annotation of informative/non-informative frames of the WCE video with less than 100 clicks |
| Address |
Las Palmas de Gran Canaria. Spain |
| Corporate Author |
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Thesis |
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| Publisher |
Springer |
Place of Publication |
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Editor |
Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario |
| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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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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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
IbPRIA |
| Notes |
MILAB;OR;MV |
Approved |
no |
| Call Number |
Admin @ si @ DSM2011 |
Serial |
1734 |
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| Author |
Lluis Pere de las Heras; Gemma Sanchez |
| Title |
And-Or Graph Grammar for Architectural Floorplan Representation, Learning and Recognition. A Semantic, Structural and Hierarchical Model |
Type |
Conference Article |
| Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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| Volume |
6669 |
Issue |
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Pages |
17-24 |
| Keywords |
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| Abstract |
This paper presents a syntactic model for architectural floor plan interpretation. A stochastic image grammar over an And-Or graph is inferred to represent the hierarchical, structural and semantic relations between elements of all possible floor plans. This grammar is augmented with three different probabilistic models, learnt from a training set, to account the frequency of that relations. Then, a Bottom-Up/Top-Down parser with a pruning strategy has been used for floor plan recognition. For a given input, the parser generates the most probable parse graph for that document. This graph not only contains the structural and semantic relations of its elements, but also its hierarchical composition, that allows to interpret the floor plan at different levels of abstraction. |
| Address |
Las Palmas de Gran Canaria. Spain |
| 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 |
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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 |
978-3-642-21256-7 |
Medium |
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| Area |
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Expedition |
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Conference |
IbPRIA |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ HeS2011 |
Serial |
1736 |
| Permanent link to this record |
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| Author |
David Fernandez; Josep Llados; Alicia Fornes |
| Title |
Handwritten Word Spotting in Old Manuscript Images Using a Pseudo-Structural Descriptor Organized in a Hash Structure |
Type |
Conference Article |
| Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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| Volume |
6669 |
Issue |
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Pages |
628-635 |
| Keywords |
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| Abstract |
There are lots of historical handwritten documents with information that can be used for several studies and projects. The Document Image Analysis and Recognition community is interested in preserving these documents and extracting all the valuable information from them. Handwritten word-spotting is the pattern classification task which consists in detecting handwriting word images. In this work, we have used a query-by-example formalism: we have matched an input image with one or multiple images from handwritten documents to determine the distance that might indicate a correspondence. We have developed an approach based in characteristic Loci Features stored in a hash structure. Document images of the marriage licences of the Cathedral of Barcelona are used as the benchmarking database. |
| Address |
Las Palmas de Gran Canaria. Spain |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
| 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 |
978-3-642-21256-7 |
Medium |
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| Area |
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Expedition |
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Conference |
IbPRIA |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ FLF2011 |
Serial |
1742 |
| Permanent link to this record |
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| Author |
Sergio Escalera; David M.J. Tax; Oriol Pujol; Petia Radeva; Robert P.W. Duin |
| Title |
Multi-Class Classification in Image Analysis Via Error-Correcting Output Codes |
Type |
Book Chapter |
| Year |
2011 |
Publication |
Innovations in Intelligent Image Analysis |
Abbreviated Journal |
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| Volume |
339 |
Issue |
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Pages |
7-29 |
| Keywords |
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| Abstract |
A common way to model multi-class classification problems is by means of Error-Correcting Output Codes (ECOC). Given a multi-class problem, the ECOC technique designs a codeword for each class, where each position of the code identifies the membership of the class for a given binary problem.A classification decision is obtained by assigning the label of the class with the closest code. In this paper, we overview the state-of-the-art on ECOC designs and test them in real applications. Results on different multi-class data sets show the benefits of using the ensemble of classifiers when categorizing objects in images. |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
Berlin |
Editor |
H. Kawasnicka; L.Jain |
| 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 |
1860-949X |
ISBN |
978-3-642-17933-4 |
Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
Admin @ si @ ETP2011 |
Serial |
1746 |
| Permanent link to this record |
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| Author |
Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga |
| Title |
Saliency Estimation Using a Non-Parametric Low-Level Vision Model |
Type |
Conference Article |
| Year |
2011 |
Publication |
IEEE conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
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| Volume |
|
Issue |
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Pages |
433-440 |
| Keywords |
Gaussian mixture model;ad hoc parameter selection;center-surround inhibition windows;center-surround mechanism;color appearance model;convolution;eye-fixation data;human vision;innate spatial pooling mechanism;inverse wavelet transform;low-level visual front-end;nonparametric low-level vision model;saliency estimation;saliency map;scale integration;scale-weighted center-surround response;scale-weighting function;visual task;Gaussian processes;biology;biology computing;colour vision;computer vision;visual perception;wavelet transforms |
| Abstract |
Many successful models for predicting attention in a scene involve three main steps: convolution with a set of filters, a center-surround mechanism and spatial pooling to construct a saliency map. However, integrating spatial information and justifying the choice of various parameter values remain open problems. In this paper we show that an efficient model of color appearance in human vision, which contains a principled selection of parameters as well as an innate spatial pooling mechanism, can be generalized to obtain a saliency model that outperforms state-of-the-art models. Scale integration is achieved by an inverse wavelet transform over the set of scale-weighted center-surround responses. The scale-weighting function (termed ECSF) has been optimized to better replicate psychophysical data on color appearance, and the appropriate sizes of the center-surround inhibition windows have been determined by training a Gaussian Mixture Model on eye-fixation data, thus avoiding ad-hoc parameter selection. Additionally, we conclude that the extension of a color appearance model to saliency estimation adds to the evidence for a common low-level visual front-end for different visual tasks. |
| Address |
Colorado Springs |
| Corporate Author |
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Thesis |
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Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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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 |
978-1-4577-0394-2 |
Medium |
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Expedition |
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Conference |
CVPR |
| Notes |
CIC |
Approved |
no |
| Call Number |
Admin @ si @ MVO2011 |
Serial |
1757 |
| Permanent link to this record |
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| Author |
Fadi Dornaika; Bogdan Raducanu |
| Title |
Subtle Facial Expression Recognition in Still Images and Videos |
Type |
Book Chapter |
| Year |
2011 |
Publication |
Advances in Face Image Analysis: Techniques and Technologies |
Abbreviated Journal |
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| Volume |
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Issue |
14 |
Pages |
259-277 |
| Keywords |
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| Abstract |
This chapter addresses the recognition of basic facial expressions. It has three main contributions. First, the authors introduce a view- and texture independent schemes that exploits facial action parameters estimated by an appearance-based 3D face tracker. they represent the learned facial actions associated with different facial expressions by time series. Two dynamic recognition schemes are proposed: (1) the first is based on conditional predictive models and on an analysis-synthesis scheme, and (2) the second is based on examples allowing straightforward use of machine learning approaches. Second, the authors propose an efficient recognition scheme based on the detection of keyframes in videos. Third, the authors compare the dynamic scheme with a static one based on analyzing individual snapshots and show that in general the former performs better than the latter. The authors then provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM). |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
IGI-Global |
Place of Publication |
New York, USA |
Editor |
Yu-Jin Zhang |
| 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 Issue |
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Edition |
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ISBN |
978-1-6152-0991-0 |
Medium |
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Expedition |
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Conference |
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| Notes |
OR;MV |
Approved |
no |
| Call Number |
Admin @ si @ DoR2011 |
Serial |
1751 |
| Permanent link to this record |
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| Author |
Xavier Perez Sala; Cecilio Angulo; Sergio Escalera |
| Title |
Biologically Inspired Turn Control in Robot Navigation |
Type |
Conference Article |
| Year |
2011 |
Publication |
14th Congrès Català en Intel·ligencia Artificial |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
187-196 |
| Keywords |
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| Abstract |
An exportable and robust system for turn control using only camera images is proposed for path execution in robot navigation. Robot motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames in the image sequence. This information is used to compute the instantaneous rotation angle. Finally, control loop is closed correcting robot displacements when it is requested for a turn command. The proposed system has been successfully tested on the four-legged Sony Aibo robot. |
| Address |
Lleida |
| 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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ISBN |
978-1-60750-841-0 |
Medium |
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| Area |
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Expedition |
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Conference |
CCIA |
| Notes |
HuPBA;MILAB |
Approved |
no |
| Call Number |
Admin @ si @ PAE2011a |
Serial |
1753 |
| Permanent link to this record |
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| Author |
Antonio Hernandez; Carlo Gatta; Laura Igual; Sergio Escalera; Petia Radeva |
| Title |
Automatic Angiography Segmentation Based on Improved Graph-cut |
Type |
Conference Article |
| Year |
2011 |
Publication |
Jornada TIC Salut Girona |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Abstract |
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Thesis |
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Place of Publication |
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Editor |
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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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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
TICGI |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
Admin @ si @ HGI2011 |
Serial |
1754 |
| Permanent link to this record |
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| Author |
Laura Igual; Antonio Hernandez; Sergio Escalera; Miguel Reyes; Josep Moya; Joan Carles Soliva; Jordi Faquet; Oscar Vilarroya; Petia Radeva |
| Title |
Automatic Techniques for Studying Attention-Deficit/Hyperactivity Disorder |
Type |
Conference Article |
| Year |
2011 |
Publication |
Jornada TIC Salut Girona |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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Thesis |
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Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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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 |
TICGI |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
Admin @ si @ IHE2011 |
Serial |
1755 |
| Permanent link to this record |
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| Author |
David Vazquez; Antonio Lopez; Daniel Ponsa; Javier Marin |
| Title |
Cool world: domain adaptation of virtual and real worlds for human detection using active learning |
Type |
Conference Article |
| Year |
2011 |
Publication |
NIPS Domain Adaptation Workshop: Theory and Application |
Abbreviated Journal |
NIPS-DA |
| Volume |
|
Issue |
|
Pages |
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| Keywords |
Pedestrian Detection; Virtual; Domain Adaptation; Active Learning |
| Abstract |
Image based human detection is of paramount interest for different applications. The most promising human detectors rely on discriminatively learnt classifiers, i.e., trained with labelled samples. However, labelling is a manual intensive task, especially in cases like human detection where it is necessary to provide at least bounding boxes framing the humans for training. To overcome such problem, in Marin et al. we have proposed the use of a virtual world where the labels of the different objects are obtained automatically. This means that the human models (classifiers) are learnt using the appearance of realistic computer graphics. Later, these models are used for human detection in images of the real world. The results of this technique are surprisingly good. However, these are not always as good as the classical approach of training and testing with data coming from the same camera and the same type of scenario. Accordingly, in Vazquez et al. we cast the problem as one of supervised domain adaptation. In doing so, we assume that a small amount of manually labelled samples from real-world images is required. To collect these labelled samples we use an active learning technique. Thus, ultimately our human model is learnt by the combination of virtual- and real-world labelled samples which, to the best of our knowledge, was not done before. Here, we term such combined space cool world. In this extended abstract we summarize our proposal, and include quantitative results from Vazquez et al. showing its validity. |
| Address |
Granada, Spain |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
Granada, Spain |
Editor |
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| Language |
English |
Summary Language |
English |
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 |
DA-NIPS |
| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ VLP2011b |
Serial |
1756 |
| Permanent link to this record |
