| Records |
| Author |
Xavier Baro; Sergio Escalera; Petia Radeva; Jordi Vitria |
| Title |
Generic Object Recognition in Urban Image Databases |
Type |
Conference Article |
| Year |
2009 |
Publication |
12th International Conference of the Catalan Association for Artificial Intelligence |
Abbreviated Journal |
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| Volume |
202 |
Issue |
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Pages |
27-34 |
| Keywords |
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| Abstract |
In this paper we propose the construction of a visual content layer which describes the visual appearance of geographic locations in a city. We captured, by means of a Mobile Mapping system, a huge set of georeferenced images (>500K) which cover the whole city of Barcelona. For each image, hundreds of region descriptions are computed off-line and described as a hash code. All this information is extracted without an object of reference, which allows to search for any type of objects using their visual appearance. A new Visual Content layer is built over Google Maps, allowing the object recognition information to be organized and fused with other content, like satellite images, street maps, and business locations. |
| Address |
Cardona (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 |
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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 |
978-1-60750-061-2 |
Medium |
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| Area |
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Expedition  |
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Conference |
CCIA |
| Notes |
OR;MILAB;HuPBA;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ VER2009 |
Serial |
1183 |
| Permanent link to this record |
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| Author |
Sergio Escalera; Alicia Fornes; Oriol Pujol; Alberto Escudero; Petia Radeva |
| Title |
Circular Blurred Shape Model for Symbol Spotting in Documents |
Type |
Conference Article |
| Year |
2009 |
Publication |
16th IEEE International Conference on Image Processing |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
1985-1988 |
| Keywords |
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| Abstract |
Symbol spotting problem requires feature extraction strategies able to generalize from training samples and to localize the target object while discarding most part of the image. In the case of document analysis, symbol spotting techniques have to deal with a high variability of symbols' appearance. In this paper, we propose the Circular Blurred Shape Model descriptor. Feature extraction is performed capturing the spatial arrangement of significant object characteristics in a correlogram structure. Shape information from objects is shared among correlogram regions, being tolerant to the irregular deformations. Descriptors are learnt using a cascade of classifiers and Abadoost as the base classifier. Finally, symbol spotting is performed by means of a windowing strategy using the learnt cascade over plan and old musical score documents. Spotting and multi-class categorization results show better performance comparing with the state-of-the-art descriptors. |
| Address |
Cairo, Egypt |
| 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 |
978-1-4244-5653-6 |
Medium |
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| Area |
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Expedition |
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Conference |
ICIP |
| Notes |
MILAB;HuPBA;DAG |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ EFP2009b |
Serial |
1184 |
| Permanent link to this record |
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| |
| Author |
Mehdi Mirza-Mohammadi; Sergio Escalera; Petia Radeva |
| Title |
Contextual-Guided Bag-of-Visual-Words Model for Multi-class Object Categorization |
Type |
Conference Article |
| Year |
2009 |
Publication |
13th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
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| Volume |
5702 |
Issue |
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Pages |
748–756 |
| Keywords |
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| Abstract |
Bag-of-words model (BOW) is inspired by the text classification problem, where a document is represented by an unsorted set of contained words. Analogously, in the object categorization problem, an image is represented by an unsorted set of discrete visual words (BOVW). In these models, relations among visual words are performed after dictionary construction. However, close object regions can have far descriptions in the feature space, being grouped as different visual words. In this paper, we present a method for considering geometrical information of visual words in the dictionary construction step. Object interest regions are obtained by means of the Harris-Affine detector and then described using the SIFT descriptor. Afterward, a contextual-space and a feature-space are defined, and a merging process is used to fuse feature words based on their proximity in the contextual-space. Moreover, we use the Error Correcting Output Codes framework to learn the new dictionary in order to perform multi-class classification. Results show significant classification improvements when spatial information is taken into account in the dictionary construction step. |
| Address |
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| 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 |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-03766-5 |
Medium |
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| Area |
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Expedition |
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Conference |
CAIP |
| Notes |
HuPBA; MILAB |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ MEP2009 |
Serial |
1185 |
| Permanent link to this record |
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| |
| Author |
Sergio Escalera; Alicia Fornes; Oriol Pujol; Petia Radeva |
| Title |
Multi-class Binary Symbol Classification with Circular Blurred Shape Models |
Type |
Conference Article |
| Year |
2009 |
Publication |
15th International Conference on Image Analysis and Processing |
Abbreviated Journal |
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| Volume |
5716 |
Issue |
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Pages |
1005–1014 |
| Keywords |
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| Abstract |
Multi-class binary symbol classification requires the use of rich descriptors and robust classifiers. Shape representation is a difficult task because of several symbol distortions, such as occlusions, elastic deformations, gaps or noise. In this paper, we present the Circular Blurred Shape Model descriptor. This descriptor encodes the arrangement information of object parts in a correlogram structure. A prior blurring degree defines the level of distortion allowed to the symbol. Moreover, we learn the new feature space using a set of Adaboost classifiers, which are combined in the Error-Correcting Output Codes framework to deal with the multi-class categorization problem. The presented work has been validated over different multi-class data sets, and compared to the state-of-the-art descriptors, showing significant performance improvements. |
| Address |
Salerno, Italy |
| 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 |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-04145-7 |
Medium |
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| Area |
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Expedition |
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Conference |
ICIAP |
| Notes |
MILAB;HuPBA;DAG |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ EFP2009c |
Serial |
1186 |
| Permanent link to this record |
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| Author |
Maria Salamo; Sergio Escalera; Petia Radeva |
| Title |
Quality Enhancement based on Reinforcement Learning and Feature Weighting for a Critiquing-Based Recommender |
Type |
Conference Article |
| Year |
2009 |
Publication |
8th International Conference on Case-Based Reasoning |
Abbreviated Journal |
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| Volume |
5650 |
Issue |
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Pages |
298–312 |
| Keywords |
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| Abstract |
Personalizing the product recommendation task is a major focus of research in the area of conversational recommender systems. Conversational case-based recommender systems help users to navigate through product spaces, alternatively making product suggestions and eliciting users feedback. Critiquing is a common form of feedback and incremental critiquing-based recommender system has shown its efficiency to personalize products based primarily on a quality measure. This quality measure influences the recommendation process and it is obtained by the combination of compatibility and similarity scores. In this paper, we describe new compatibility strategies whose basis is on reinforcement learning and a new feature weighting technique which is based on the user’s history of critiques. Moreover, we show that our methodology can significantly improve recommendation efficiency in comparison with the state-of-the-art approaches. |
| Address |
Seattle, USA |
| 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 |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-02998-1 |
Medium |
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| Area |
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Expedition |
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Conference |
ICCBR |
| Notes |
HuPBA; MILAB |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ SER2009 |
Serial |
1187 |
| Permanent link to this record |
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| Author |
Sergio Escalera; Eloi Puertas; Petia Radeva; Oriol Pujol |
| Title |
Multimodal laughter recognition in video conversations |
Type |
Conference Article |
| Year |
2009 |
Publication |
2nd IEEE Workshop on CVPR for Human communicative Behavior analysis |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
110–115 |
| Keywords |
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| Abstract |
Laughter detection is an important area of interest in the Affective Computing and Human-computer Interaction fields. In this paper, we propose a multi-modal methodology based on the fusion of audio and visual cues to deal with the laughter recognition problem in face-to-face conversations. The audio features are extracted from the spectogram and the video features are obtained estimating the mouth movement degree and using a smile and laughter classifier. Finally, the multi-modal cues are included in a sequential classifier. Results over videos from the public discussion blog of the New York Times show that both types of features perform better when considered together by the classifier. Moreover, the sequential methodology shows to significantly outperform the results obtained by an Adaboost classifier. |
| Address |
Miami (USA) |
| 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 |
2160-7508 |
ISBN |
978-1-4244-3994-2 |
Medium |
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| Area |
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Expedition |
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Conference |
CVPR |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ EPR2009c |
Serial |
1188 |
| Permanent link to this record |
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| Author |
Xavier Baro; Sergio Escalera; Petia Radeva; Jordi Vitria |
| Title |
Visual Content Layer for Scalable Recognition in Urban Image Databases, Internet Multimedia Search and Mining |
Type |
Conference Article |
| Year |
2009 |
Publication |
10th IEEE International Conference on Multimedia and Expo |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
1616–1619 |
| Keywords |
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| Abstract |
Rich online map interaction represents a useful tool to get multimedia information related to physical places. With this type of systems, users can automatically compute the optimal route for a trip or to look for entertainment places or hotels near their actual position. Standard maps are defined as a fusion of layers, where each one contains specific data such height, streets, or a particular business location. In this paper we propose the construction of a visual content layer which describes the visual appearance of geographic locations in a city. We captured, by means of a Mobile Mapping system, a huge set of georeferenced images (> 500K) which cover the whole city of Barcelona. For each image, hundreds of region descriptions are computed off-line and described as a hash code. This allows an efficient and scalable way of accessing maps by visual content. |
| Address |
New York (USA) |
| 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 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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| ISSN |
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ISBN |
978-1-4244-4291-1 |
Medium |
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| Area |
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Expedition |
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Conference |
ICME |
| Notes |
OR;MILAB;HuPBA;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ BER2009 |
Serial |
1189 |
| Permanent link to this record |
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| Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
| Title |
Recoding Error-Correcting Output Codes |
Type |
Conference Article |
| Year |
2009 |
Publication |
8th International Workshop of Multiple Classifier Systems |
Abbreviated Journal |
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| Volume |
5519 |
Issue |
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Pages |
11–21 |
| Keywords |
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| Abstract |
One of the most widely applied techniques to deal with multi- class categorization problems is the pairwise voting procedure. Recently, this classical approach has been embedded in the Error-Correcting Output Codes framework (ECOC). This framework is based on a coding step, where a set of binary problems are learnt and coded in a matrix, and a decoding step, where a new sample is tested and classified according to a comparison with the positions of the coded matrix. In this paper, we present a novel approach to redefine without retraining, in a problem-dependent way, the one-versus-one coding matrix so that the new coded information increases the generalization capability of the system. Moreover, the final classification can be tuned with the inclusion of a weighting matrix in the decoding step. The approach has been validated over several UCI Machine Learning repository data sets and two real multi-class problems: traffic sign and face categorization. The results show that performance improvements are obtained when comparing the new approach to one of the best ECOC designs (one-versus-one). Furthermore, the novel methodology obtains at least the same performance than the one-versus-one ECOC design. |
| Address |
Reykjavik (Iceland) |
| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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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 Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-02325-5 |
Medium |
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| Area |
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Expedition |
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Conference |
MCS |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ EPR2009d |
Serial |
1190 |
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| Author |
Javier Vazquez; C. Alejandro Parraga; Maria Vanrell |
| Title |
Ordinal pairwise method for natural images comparison |
Type |
Journal Article |
| Year |
2009 |
Publication |
Perception |
Abbreviated Journal |
PER |
| Volume |
38 |
Issue |
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Pages |
180 |
| Keywords |
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| Abstract |
38(Suppl.)ECVP Abstract Supplement
We developed a new psychophysical method to compare different colour appearance models when applied to natural scenes. The method was as follows: two images (processed by different algorithms) were displayed on a CRT monitor and observers were asked to select the most natural of them. The original images were gathered by means of a calibrated trichromatic digital camera and presented one on top of the other on a calibrated screen. The selection was made by pressing on a 6-button IR box, which allowed observers to consider not only the most natural but to rate their selection. The rating system allowed observers to register how much more natural was their chosen image (eg, much more, definitely more, slightly more), which gave us valuable extra information on the selection process. The results were analysed considering both the selection as a binary choice (using Thurstone's law of comparative judgement) and using Bradley-Terry method for ordinal comparison. Our results show a significant difference in the rating scales obtained. Although this method has been used in colour constancy algorithm comparisons, its uses are much wider, eg to compare algorithms of image compression, rendering, recolouring, etc. |
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CIC |
Approved |
no |
| Call Number |
CAT @ cat @ VPV2009b |
Serial |
1191 |
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| Author |
Robert Benavente; C. Alejandro Parraga; Maria Vanrell |
| Title |
Colour categories boundaries are better defined in contextual conditions |
Type |
Journal Article |
| Year |
2009 |
Publication |
Perception |
Abbreviated Journal |
PER |
| Volume |
38 |
Issue |
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Pages |
36 |
| Keywords |
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| Abstract |
In a previous experiment [Parraga et al, 2009 Journal of Imaging Science and Technology 53(3)] the boundaries between basic colour categories were measured by asking subjects to categorize colour samples presented in isolation (ie on a dark background) using a YES/NO paradigm. Results showed that some boundaries (eg green – blue) were very diffuse and the subjects' answers presented bimodal distributions, which were attributed to the emergence of non-basic categories in those regions (eg turquoise). To confirm these results we performed a new experiment focussed on the boundaries where bimodal distributions were more evident. In this new experiment rectangular colour samples were presented surrounded by random colour patches to simulate contextual conditions on a calibrated CRT monitor. The names of two neighbouring colours were shown at the bottom of the screen and subjects selected the boundary between these colours by controlling the chromaticity of the central patch, sliding it across these categories' frontier. Results show that in this new experimental paradigm, the formerly uncertain inter-colour category boundaries are better defined and the dispersions (ie the bimodal distributions) that occurred in the previous experiment disappear. These results may provide further support to Berlin and Kay's basic colour terms theory. |
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CIC |
Approved |
no |
| Call Number |
CAT @ cat @ BPV2009 |
Serial |
1192 |
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| Author |
C. Alejandro Parraga; Javier Vazquez; Maria Vanrell |
| Title |
A new cone activation-based natural images dataset |
Type |
Journal Article |
| Year |
2009 |
Publication |
Perception |
Abbreviated Journal |
PER |
| Volume |
36 |
Issue |
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Pages |
180 |
| Keywords |
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| Abstract |
We generated a new dataset of digital natural images where each colour plane corresponds to the human LMS (long-, medium-, short-wavelength) cone activations. The images were chosen to represent five different visual environments (eg forest, seaside, mountain snow, urban, motorways) and were taken under natural illumination at different times of day. At the bottom-left corner of each picture there was a matte grey ball of approximately constant spectral reflectance (across the camera's response spectrum,) and nearly Lambertian reflective properties, which allows to compute (and remove, if necessary) the illuminant's colour and intensity. The camera (Sigma Foveon SD10) was calibrated by measuring its sensor's spectral responses using a set of 31 spectrally narrowband interference filters. This allowed conversion of the final camera-dependent RGB colour space into the Smith and Pokorny (1975) cone activation space by means of a polynomial transformation, optimised for a set of 1269 Munsell chip reflectances. This new method is an improvement over the usual 3 × 3 matrix transformation which is only accurate for spectrally-narrowband colours. The camera-to-LMS transformation can be recalculated to consider other non-human visual systems. The dataset is available to download from our website. |
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CIC |
Approved |
no |
| Call Number |
CAT @ cat @ PVV2009 |
Serial |
1193 |
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| Author |
Mohammad Rouhani; Angel Sappa |
| Title |
A Novel Approach to Geometric Fitting of Implicit Quadrics |
Type |
Conference Article |
| Year |
2009 |
Publication |
8th International Conference on Advanced Concepts for Intelligent Vision Systems |
Abbreviated Journal |
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| Volume |
5807 |
Issue |
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Pages |
121–132 |
| Keywords |
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| Abstract |
This paper presents a novel approach for estimating the geometric distance from a given point to the corresponding implicit quadric curve/surface. The proposed estimation is based on the height of a tetrahedron, which is used as a coarse but reliable estimation of the real distance. The estimated distance is then used for finding the best set of quadric parameters, by means of the Levenberg-Marquardt algorithm, which is a common framework in other geometric fitting approaches. Comparisons of the proposed approach with previous ones are provided to show both improvements in CPU time as well as in the accuracy of the obtained results. |
| Address |
Bordeaux, France |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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LNCS |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-04696-4 |
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Conference |
ACIVS |
| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ RoS2009 |
Serial |
1194 |
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| Author |
Joost Van de Weijer; Cordelia Schmid; Jakob Verbeek; Diane Larlus |
| Title |
Learning Color Names for Real-World Applications |
Type |
Journal Article |
| Year |
2009 |
Publication |
IEEE Transaction in Image Processing |
Abbreviated Journal |
TIP |
| Volume |
18 |
Issue |
7 |
Pages |
1512–1524 |
| Keywords |
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| Abstract |
Color names are required in real-world applications such as image retrieval and image annotation. Traditionally, they are learned from a collection of labelled color chips. These color chips are labelled with color names within a well-defined experimental setup by human test subjects. However naming colors in real-world images differs significantly from this experimental setting. In this paper, we investigate how color names learned from color chips compare to color names learned from real-world images. To avoid hand labelling real-world images with color names we use Google Image to collect a data set. Due to limitations of Google Image this data set contains a substantial quantity of wrongly labelled data. We propose several variants of the PLSA model to learn color names from this noisy data. Experimental results show that color names learned from real-world images significantly outperform color names learned from labelled color chips for both image retrieval and image annotation. |
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Series Title |
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Series Issue |
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Edition |
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| ISSN |
1057-7149 |
ISBN |
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| Notes |
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Approved |
no |
| Call Number |
CAT @ cat @ WSV2009 |
Serial |
1195 |
| Permanent link to this record |
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| Author |
Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell |
| Title |
Top-Down Color Attention for Object Recognition |
Type |
Conference Article |
| Year |
2009 |
Publication |
12th International Conference on Computer Vision |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
979 - 986 |
| Keywords |
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| Abstract |
Generally the bag-of-words based image representation follows a bottom-up paradigm. The subsequent stages of the process: feature detection, feature description, vocabulary construction and image representation are performed independent of the intentioned object classes to be detected. In such a framework, combining multiple cues such as shape and color often provides below-expected results. This paper presents a novel method for recognizing object categories when using multiple cues by separating the shape and color cue. Color is used to guide attention by means of a top-down category-specific attention map. The color attention map is then further deployed to modulate the shape features by taking more features from regions within an image that are likely to contain an object instance. This procedure leads to a category-specific image histogram representation for each category. Furthermore, we argue that the method combines the advantages of both early and late fusion. We compare our approach with existing methods that combine color and shape cues on three data sets containing varied importance of both cues, namely, Soccer ( color predominance), Flower (color and shape parity), and PASCAL VOC Challenge 2007 (shape predominance). The experiments clearly demonstrate that in all three data sets our proposed framework significantly outperforms the state-of-the-art methods for combining color and shape information. |
| Address |
Kyoto, Japan |
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Edition |
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| ISSN |
1550-5499 |
ISBN |
978-1-4244-4420-5 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
ICCV |
| Notes |
CIC |
Approved |
no |
| Call Number |
CAT @ cat @ SWV2009 |
Serial |
1196 |
| Permanent link to this record |
| |
|
| |
| Author |
Arjan Gijsenij; Theo Gevers; Joost Van de Weijer |
| Title |
Physics-based Edge Evaluation for Improved Color Constancy |
Type |
Conference Article |
| Year |
2009 |
Publication |
22nd IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
581 – 588 |
| Keywords |
|
| Abstract |
Edge-based color constancy makes use of image derivatives to estimate the illuminant. However, different edge types exist in real-world images such as shadow, geometry, material and highlight edges. These different edge types may have a distinctive influence on the performance of the illuminant estimation. |
| Address |
Miami, USA |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
1063-6919 |
ISBN |
978-1-4244-3992-8 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
CVPR |
| Notes |
CAT;ISE |
Approved |
no |
| Call Number |
CAT @ cat @ GGW2009 |
Serial |
1197 |
| Permanent link to this record |
