| Records |
| Author |
Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez |
| Title |
Determining the Best Suited Semantic Events for Cognitive Surveillance |
Type |
Journal Article |
| Year |
2011 |
Publication |
Expert Systems with Applications |
Abbreviated Journal |
EXSY |
| Volume |
38 |
Issue |
4 |
Pages |
4068–4079 |
| Keywords |
Cognitive surveillance; Event modeling; Content-based video retrieval; Ontologies; Advanced user interfaces |
| Abstract |
State-of-the-art systems on cognitive surveillance identify and describe complex events in selected domains, thus providing end-users with tools to easily access the contents of massive video footage. Nevertheless, as the complexity of events increases in semantics and the types of indoor/outdoor scenarios diversify, it becomes difficult to assess which events describe better the scene, and how to model them at a pixel level to fulfill natural language requests. We present an ontology-based methodology that guides the identification, step-by-step modeling, and generalization of the most relevant events to a specific domain. Our approach considers three steps: (1) end-users provide textual evidence from surveilled video sequences; (2) transcriptions are analyzed top-down to build the knowledge bases for event description; and (3) the obtained models are used to generalize event detection to different image sequences from the surveillance domain. This framework produces user-oriented knowledge that improves on existing advanced interfaces for video indexing and retrieval, by determining the best suited events for video understanding according to end-users. We have conducted experiments with outdoor and indoor scenes showing thefts, chases, and vandalism, demonstrating the feasibility and generalization of this proposal. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Elsevier |
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 |
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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 @ FBR2011a |
Serial |
1722 |
| Permanent link to this record |
| |
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| |
| Author |
Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez |
| Title |
Augmenting Video Surveillance Footage with Virtual Agents for Incremental Event Evaluation |
Type |
Journal Article |
| Year |
2011 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
32 |
Issue |
6 |
Pages |
878–889 |
| Keywords |
|
| Abstract |
The fields of segmentation, tracking and behavior analysis demand for challenging video resources to test, in a scalable manner, complex scenarios like crowded environments or scenes with high semantics. Nevertheless, existing public databases cannot scale the presence of appearing agents, which would be useful to study long-term occlusions and crowds. Moreover, creating these resources is expensive and often too particularized to specific needs. We propose an augmented reality framework to increase the complexity of image sequences in terms of occlusions and crowds, in a scalable and controllable manner. Existing datasets can be increased with augmented sequences containing virtual agents. Such sequences are automatically annotated, thus facilitating evaluation in terms of segmentation, tracking, and behavior recognition. In order to easily specify the desired contents, we propose a natural language interface to convert input sentences into virtual agent behaviors. Experimental tests and validation in indoor, street, and soccer environments are provided to show the feasibility of the proposed approach in terms of robustness, scalability, and semantics. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Elsevier |
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 |
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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 @ FBR2011b |
Serial |
1723 |
| Permanent link to this record |
| |
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| |
| Author |
Alicia Fornes; Anjan Dutta; Albert Gordo; Josep Llados |
| Title |
The ICDAR 2011 Music Scores Competition: Staff Removal and Writer Identification |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
1511-1515 |
| Keywords |
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| Abstract |
In the last years, there has been a growing interest in the analysis of handwritten music scores. In this sense, our goal has been to foster the interest in the analysis of handwritten music scores by the proposal of two different competitions: Staff removal and Writer Identification. Both competitions have been tested on the CVC-MUSCIMA database: a ground-truth of handwritten music score images. This paper describes the competition details, including the dataset and ground-truth, the evaluation metrics, and a short description of the participants, their methods, and the obtained results. |
| Address |
Beijing, China |
| 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 |
|
ISBN |
978-0-7695-4520-2 |
Medium |
|
| Area |
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Expedition |
|
Conference |
ICDAR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ FDG2011b |
Serial |
1794 |
| Permanent link to this record |
| |
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| |
| Author |
Volkmar Frinken; Andreas Fischer; Horst Bunke; Alicia Fornes |
| Title |
Co-training for Handwritten Word Recognition |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
314-318 |
| Keywords |
|
| Abstract |
To cope with the tremendous variations of writing styles encountered between different individuals, unconstrained automatic handwriting recognition systems need to be trained on large sets of labeled data. Traditionally, the training data has to be labeled manually, which is a laborious and costly process. Semi-supervised learning techniques offer methods to utilize unlabeled data, which can be obtained cheaply in large amounts in order, to reduce the need for labeled data. In this paper, we propose the use of Co-Training for improving the recognition accuracy of two weakly trained handwriting recognition systems. The first one is based on Recurrent Neural Networks while the second one is based on Hidden Markov Models. On the IAM off-line handwriting database we demonstrate a significant increase of the recognition accuracy can be achieved with Co-Training for single word recognition. |
| Address |
Beijing, China |
| 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 |
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Medium |
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| Area |
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Expedition |
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Conference |
ICDAR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ FFB2011 |
Serial |
1789 |
| Permanent link to this record |
| |
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| |
| Author |
Alicia Fornes; Volkmar Frinken; Andreas Fischer; Jon Almazan; G. Jackson; Horst Bunke |
| Title |
A Keyword Spotting Approach Using Blurred Shape Model-Based Descriptors |
Type |
Conference Article |
| Year |
2011 |
Publication |
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
83-90 |
| Keywords |
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| Abstract |
The automatic processing of handwritten historical documents is considered a hard problem in pattern recognition. In addition to the challenges given by modern handwritten data, a lack of training data as well as effects caused by the degradation of documents can be observed. In this scenario, keyword spotting arises to be a viable solution to make documents amenable for searching and browsing. For this task we propose the adaptation of shape descriptors used in symbol recognition. By treating each word image as a shape, it can be represented using the Blurred Shape Model and the De-formable Blurred Shape Model. Experiments on the George Washington database demonstrate that this approach is able to outperform the commonly used Dynamic Time Warping approach. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
ACM |
Place of Publication |
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Editor |
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| Language |
|
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 |
|
ISBN |
978-1-4503-0916-5 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
HIP |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ FFF2011a |
Serial |
1823 |
| Permanent link to this record |
| |
|
| |
| Author |
Andreas Fischer; Volkmar Frinken; Alicia Fornes; Horst Bunke |
| Title |
Transcription Alignment of Latin Manuscripts Using Hidden Markov Models |
Type |
Conference Article |
| Year |
2011 |
Publication |
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
29-36 |
| Keywords |
|
| Abstract |
Transcriptions of historical documents are a valuable source for extracting labeled handwriting images that can be used for training recognition systems. In this paper, we introduce the Saint Gall database that includes images as well as the transcription of a Latin manuscript from the 9th century written in Carolingian script. Although the available transcription is of high quality for a human reader, the spelling of the words is not accurate when compared with the handwriting image. Hence, the transcription poses several challenges for alignment regarding, e.g., line breaks, abbreviations, and capitalization. We propose an alignment system based on character Hidden Markov Models that can cope with these challenges and efficiently aligns complete document pages. On the Saint Gall database, we demonstrate that a considerable alignment accuracy can be achieved, even with weakly trained character models. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
ACM |
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 |
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Medium |
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| Area |
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Expedition |
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Conference |
HIP |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ FFF2011b |
Serial |
1824 |
| 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 |
|
| Volume |
6669 |
Issue |
|
Pages |
628-635 |
| Keywords |
|
| 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 |
|
Place of Publication |
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Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
| Language |
|
Summary Language |
|
Original Title |
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| Series Editor |
|
Series Title |
|
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 |
|
ISBN |
978-3-642-21256-7 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
IbPRIA |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ FLF2011 |
Serial |
1742 |
| Permanent link to this record |
| |
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| |
| Author |
Wenjuan Gong; Jürgen Brauer; Michael Arens; Jordi Gonzalez |
| Title |
Modeling vs. Learning Approaches for Monocular 3D Human Pose Estimation |
Type |
Conference Article |
| Year |
2011 |
Publication |
1st IEEE International Workshop on Performance Evaluation on Recognition of Human Actions and Pose Estimation Methods |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
London, United Kingdom |
| 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 |
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Medium |
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| Area |
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Expedition |
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Conference |
PERHAPS |
| Notes |
ISE |
Approved |
no |
| Call Number |
Admin @ si @ GBA2011 |
Serial |
1812 |
| Permanent link to this record |
| |
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| |
| Author |
Carlo Gatta; Simone Balocco; Victoria Martin Yuste; Ruben Leta; Petia Radeva |
| Title |
Non-rigid Multi-modal Registration of Coronary Arteries Using SIFTflow |
Type |
Conference Article |
| Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
| Volume |
6669 |
Issue |
|
Pages |
159-166 |
| Keywords |
|
| Abstract |
The fusion of clinically relevant information coming from different image modalities is an important topic in medical imaging. In particular, different cardiac imaging modalities provides complementary information for the physician: Computer Tomography Angiography (CTA) provides reliable pre-operative information on arteries geometry, even in the presence of chronic total occlusions, while X-Ray Angiography (XRA) allows intra-operative high resolution projections of a specific artery. The non-rigid registration of arteries between these two modalities is a difficult task. In this paper we propose the use of SIFTflow, in registering CTA and XRA images. At the best of our knowledge, this paper proposed SIFTflow as a XRay-CTA registration method for the first time in the literature. To highlight the arteries, so to guide the registration process, the well known Vesselness method has been employed. Results confirm that, to the aim of registration, the arteries must be highlighted and background objects removed as much as possible. Moreover, the comparison with the well known Free Form Deformation technique, suggests that SIFTflow has a great potential in the registration of multi-modal medical images. |
| 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 |
Berlin |
Editor |
Jordi Vitria; Joao Miguel Sanches; Mario Hernandez |
| Language |
|
Summary Language |
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Original Title |
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| Series Editor |
|
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 |
978-3-642-21256-7 |
Medium |
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| Area |
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Expedition |
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Conference |
IbPRIA |
| Notes |
MILAB |
Approved |
no |
| Call Number |
Admin @ si @ GBM2011 |
Serial |
1752 |
| Permanent link to this record |
| |
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| |
| Author |
Jordi Gonzalez; Josep M. Gonfaus; Carles Fernandez; Xavier Roca |
| Title |
Exploiting Natural-Language Interaction in Video Surveillance Systems |
Type |
Conference Article |
| Year |
2011 |
Publication |
V&L Net Workshop on Vision and Language |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
Brighton, UK |
| 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 |
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Medium |
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| Area |
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Expedition |
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Conference |
VL |
| Notes |
ISE |
Approved |
no |
| Call Number |
Admin @ si @ GGF2011 |
Serial |
1813 |
| Permanent link to this record |
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| |
| Author |
Arjan Gijsenij; Theo Gevers; Joost Van de Weijer |
| Title |
Computational Color Constancy: Survey and Experiments |
Type |
Journal Article |
| Year |
2011 |
Publication |
IEEE Transactions on Image Processing |
Abbreviated Journal |
TIP |
| Volume |
20 |
Issue |
9 |
Pages |
2475-2489 |
| Keywords |
computational color constancy;computer vision application;gamut-based method;learning-based method;static method;colour vision;computer vision;image colour analysis;learning (artificial intelligence);lighting |
| Abstract |
Computational color constancy is a fundamental prerequisite for many computer vision applications. This paper presents a survey of many recent developments and state-of-the- art methods. Several criteria are proposed that are used to assess the approaches. A taxonomy of existing algorithms is proposed and methods are separated in three groups: static methods, gamut-based methods and learning-based methods. Further, the experimental setup is discussed including an overview of publicly available data sets. Finally, various freely available methods, of which some are considered to be state-of-the-art, are evaluated on two data sets. |
| Address |
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| 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 |
1057-7149 |
ISBN |
|
Medium |
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| Area |
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Expedition |
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Conference |
|
| Notes |
ISE;CIC |
Approved |
no |
| Call Number |
Admin @ si @ GGW2011 |
Serial |
1717 |
| Permanent link to this record |
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| |
| Author |
Arjan Gijsenij; Theo Gevers |
| Title |
Color Constancy Using Natural Image Statistics and Scene Semantics |
Type |
Journal Article |
| Year |
2011 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
| Volume |
33 |
Issue |
4 |
Pages |
687-698 |
| Keywords |
|
| Abstract |
Existing color constancy methods are all based on specific assumptions such as the spatial and spectral characteristics of images. As a consequence, no algorithm can be considered as universal. However, with the large variety of available methods, the question is how to select the method that performs best for a specific image. To achieve selection and combining of color constancy algorithms, in this paper natural image statistics are used to identify the most important characteristics of color images. Then, based on these image characteristics, the proper color constancy algorithm (or best combination of algorithms) is selected for a specific image. To capture the image characteristics, the Weibull parameterization (e.g., grain size and contrast) is used. It is shown that the Weibull parameterization is related to the image attributes to which the used color constancy methods are sensitive. An MoG-classifier is used to learn the correlation and weighting between the Weibull-parameters and the image attributes (number of edges, amount of texture, and SNR). The output of the classifier is the selection of the best performing color constancy method for a certain image. Experimental results show a large improvement over state-of-the-art single algorithms. On a data set consisting of more than 11,000 images, an increase in color constancy performance up to 20 percent (median angular error) can be obtained compared to the best-performing single algorithm. Further, it is shown that for certain scene categories, one specific color constancy algorithm can be used instead of the classifier considering several algorithms. |
| Address |
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| 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 |
0162-8828 |
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 @ GiG2011 |
Serial |
1724 |
| Permanent link to this record |
| |
|
| |
| Author |
Alejandro Gonzalez Alzate |
| Title |
Evaluation of spatiotemporal descriptors for pedestrian detection in video sequences |
Type |
Report |
| Year |
2011 |
Publication |
CVC Technical Report |
Abbreviated Journal |
|
| Volume |
166 |
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
|
| Address |
Bellaterra (Spain) |
| Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
| Publisher |
|
Place of Publication |
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Editor |
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| Language |
|
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 |
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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 |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ Gon2011 |
Serial |
1932 |
| Permanent link to this record |
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| |
| Author |
Albert Gordo; Florent Perronnin |
| Title |
Asymmetric Distances for Binary Embeddings |
Type |
Conference Article |
| Year |
2011 |
Publication |
IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
729 - 736 |
| Keywords |
|
| Abstract |
In large-scale query-by-example retrieval, embedding image signatures in a binary space offers two benefits: data compression and search efficiency. While most embedding algorithms binarize both query and database signatures, it has been noted that this is not strictly a requirement. Indeed, asymmetric schemes which binarize the database signatures but not the query still enjoy the same two benefits but may provide superior accuracy. In this work, we propose two general asymmetric distances which are applicable to a wide variety of embedding techniques including Locality Sensitive Hashing (LSH), Locality Sensitive Binary Codes (LSBC), Spectral Hashing (SH) and Semi-Supervised Hashing (SSH). We experiment on four public benchmarks containing up to 1M images and show that the proposed asymmetric distances consistently lead to large improvements over the symmetric Hamming distance for all binary embedding techniques. We also propose a novel simple binary embedding technique – PCA Embedding (PCAE) – which is shown to yield competitive results with respect to more complex algorithms such as SH and SSH. |
| Address |
Providence, RI |
| 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 |
|
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
|
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 |
|
ISBN |
978-1-4577-0394-2 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
CVPR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ GoP2011; IAM @ iam @ GoP2011 |
Serial |
1817 |
| Permanent link to this record |
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| |
| Author |
Carlo Gatta; Eloi Puertas; Oriol Pujol |
| Title |
Multi-Scale Stacked Sequential Learning |
Type |
Journal Article |
| Year |
2011 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
| Volume |
44 |
Issue |
10-11 |
Pages |
2414-2416 |
| Keywords |
Stacked sequential learning; Multiscale; Multiresolution; Contextual classification |
| Abstract |
One of the most widely used assumptions in supervised learning is that data is independent and identically distributed. This assumption does not hold true in many real cases. Sequential learning is the discipline of machine learning that deals with dependent data such that neighboring examples exhibit some kind of relationship. In the literature, there are different approaches that try to capture and exploit this correlation, by means of different methodologies. In this paper we focus on meta-learning strategies and, in particular, the stacked sequential learning approach. The main contribution of this work is two-fold: first, we generalize the stacked sequential learning. This generalization reflects the key role of neighboring interactions modeling. Second, we propose an effective and efficient way of capturing and exploiting sequential correlations that takes into account long-range interactions by means of a multi-scale pyramidal decomposition of the predicted labels. Additionally, this new method subsumes the standard stacked sequential learning approach. We tested the proposed method on two different classification tasks: text lines classification in a FAQ data set and image classification. Results on these tasks clearly show that our approach outperforms the standard stacked sequential learning. Moreover, we show that the proposed method allows to control the trade-off between the detail and the desired range of the interactions. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Elsevier |
Place of Publication |
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Editor |
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| Language |
|
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 |
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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 |
MILAB;HuPBA |
Approved |
no |
| Call Number |
Admin @ si @ GPP2011 |
Serial |
1802 |
| Permanent link to this record |
