| Records |
| Author |
C. Alejandro Parraga |
| Title |
Color Vision, Computational Methods for |
Type |
Book Chapter |
| Year |
2014 |
Publication |
Encyclopedia of Computational Neuroscience |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
1-11 |
| Keywords |
Color computational vision; Computational neuroscience of color |
| Abstract |
The study of color vision has been aided by a whole battery of computational methods that attempt to describe the mechanisms that lead to our perception of colors in terms of the information-processing properties of the visual system. Their scope is highly interdisciplinary, linking apparently dissimilar disciplines such as mathematics, physics, computer science, neuroscience, cognitive science, and psychology. Since the sensation of color is a feature of our brains, computational approaches usually include biological features of neural systems in their descriptions, from retinal light-receptor interaction to subcortical color opponency, cortical signal decoding, and color categorization. They produce hypotheses that are usually tested by behavioral or psychophysical experiments. |
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Thesis |
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| Publisher |
Springer-Verlag Berlin Heidelberg |
Place of Publication |
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Editor |
Dieter Jaeger; Ranu Jung |
| Language |
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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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ISBN |
978-1-4614-7320-6 |
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Expedition |
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Conference |
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| Notes |
CIC; 600.074 |
Approved |
no |
| Call Number |
Admin @ si @ Par2014 |
Serial |
2512 |
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| Author |
Miquel Ferrer; I. Bardaji; Ernest Valveny; Dimosthenis Karatzas; Horst Bunke |
| Title |
Median Graph Computation by Means of Graph Embedding into Vector Spaces |
Type |
Book Chapter |
| Year |
2013 |
Publication |
Graph Embedding for Pattern Analysis |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
45-72 |
| Keywords |
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| Abstract |
In pattern recognition [8, 14], a key issue to be addressed when designing a system is how to represent input patterns. Feature vectors is a common option. That is, a set of numerical features describing relevant properties of the pattern are computed and arranged in a vector form. The main advantages of this kind of representation are computational simplicity and a well sound mathematical foundation. Thus, a large number of operations are available to work with vectors and a large repository of algorithms for pattern analysis and classification exist. However, the simple structure of feature vectors might not be the best option for complex patterns where nonnumerical features or relations between different parts of the pattern become relevant. |
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Thesis |
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| Publisher |
Springer New York |
Place of Publication |
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Editor |
Yun Fu; Yungian Ma |
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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 |
978-1-4614-4456-5 |
Medium |
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Expedition |
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Conference |
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| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ FBV2013 |
Serial |
2421 |
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| Author |
Svebor Karaman; Giuseppe Lisanti; Andrew Bagdanov; Alberto del Bimbo |
| Title |
From re-identification to identity inference: Labeling consistency by local similarity constraints |
Type |
Book Chapter |
| Year |
2014 |
Publication |
Person Re-Identification |
Abbreviated Journal |
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| Volume |
2 |
Issue |
|
Pages |
287-307 |
| Keywords |
re-identification; Identity inference; Conditional random fields; Video surveillance |
| Abstract |
In this chapter, we introduce the problem of identity inference as a generalization of person re-identification. It is most appropriate to distinguish identity inference from re-identification in situations where a large number of observations must be identified without knowing a priori that groups of test images represent the same individual. The standard single- and multishot person re-identification common in the literature are special cases of our formulation. We present an approach to solving identity inference by modeling it as a labeling problem in a Conditional Random Field (CRF). The CRF model ensures that the final labeling gives similar labels to detections that are similar in feature space. Experimental results are given on the ETHZ, i-LIDS and CAVIAR datasets. Our approach yields state-of-the-art performance for multishot re-identification, and our results on the more general identity inference problem demonstrate that we are able to infer the identity of very many examples even with very few labeled images in the gallery. |
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Thesis |
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| Publisher |
Springer London |
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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| ISSN |
2191-6586 |
ISBN |
978-1-4471-6295-7 |
Medium |
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Expedition |
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Conference |
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| Notes |
LAMP; 600.079 |
Approved |
no |
| Call Number |
Admin @ si @KLB2014b |
Serial |
2521 |
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| Author |
Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva |
| Title |
Traffic-Sign Recognition Systems |
Type |
Book Whole |
| Year |
2011 |
Publication |
SpringerBriefs in Computer Science |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
5-13 |
| Keywords |
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| Abstract |
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| Address |
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Thesis |
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| Publisher |
Springer London |
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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| ISSN |
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ISBN |
978-1-4471-2244-9 |
Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
MILAB; OR;HuPBA;MV |
Approved |
no |
| Call Number |
Admin @ si @ EBP2011 |
Serial |
1801 |
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| Author |
Murad Al Haj; Carles Fernandez; Zhanwu Xiong; Ivan Huerta; Jordi Gonzalez; Xavier Roca |
| Title |
Beyond the Static Camera: Issues and Trends in Active Vision |
Type |
Book Chapter |
| Year |
2011 |
Publication |
Visual Analysis of Humans: Looking at People |
Abbreviated Journal |
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| Volume |
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Issue |
2 |
Pages |
11-30 |
| Keywords |
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| Abstract |
Maximizing both the area coverage and the resolution per target is highly desirable in many applications of computer vision. However, with a limited number of cameras viewing a scene, the two objectives are contradictory. This chapter is dedicated to active vision systems, trying to achieve a trade-off between these two aims and examining the use of high-level reasoning in such scenarios. The chapter starts by introducing different approaches to active cameras configurations. Later, a single active camera system to track a moving object is developed, offering the reader first-hand understanding of the issues involved. Another section discusses practical considerations in building an active vision platform, taking as an example a multi-camera system developed for a European project. The last section of the chapter reflects upon the future trends of using semantic factors to drive smartly coordinated active systems. |
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Thesis |
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| Publisher |
Springer London |
Place of Publication |
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Editor |
Th.B. Moeslund; A. Hilton; V. Krüger; L. Sigal |
| Language |
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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 |
978-0-85729-996-3 |
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 @ AFX2011 |
Serial |
1814 |
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| Author |
Nataliya Shapovalova; Carles Fernandez; Xavier Roca; Jordi Gonzalez |
| Title |
Semantics of Human Behavior in Image Sequences |
Type |
Book Chapter |
| Year |
2011 |
Publication |
Computer Analysis of Human Behavior |
Abbreviated Journal |
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| Volume |
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Issue |
7 |
Pages |
151-182 |
| Keywords |
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| Abstract |
Human behavior is contextualized and understanding the scene of an action is crucial for giving proper semantics to behavior. In this chapter we present a novel approach for scene understanding. The emphasis of this work is on the particular case of Human Event Understanding. We introduce a new taxonomy to organize the different semantic levels of the Human Event Understanding framework proposed. Such a framework particularly contributes to the scene understanding domain by (i) extracting behavioral patterns from the integrative analysis of spatial, temporal, and contextual evidence and (ii) integrative analysis of bottom-up and top-down approaches in Human Event Understanding. We will explore how the information about interactions between humans and their environment influences the performance of activity recognition, and how this can be extrapolated to the temporal domain in order to extract higher inferences from human events observed in sequences of images. |
| Address |
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Thesis |
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| Publisher |
Springer London |
Place of Publication |
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Editor |
Albert Ali Salah; |
| 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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| ISSN |
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ISBN |
978-0-85729-993-2 |
Medium |
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Expedition |
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Conference |
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| Notes |
ISE |
Approved |
no |
| Call Number |
Admin @ si @ SFR2011 |
Serial |
1810 |
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| Author |
Alicia Fornes; Gemma Sanchez |
| Title |
Analysis and Recognition of Music Scores |
Type |
Book Chapter |
| Year |
2014 |
Publication |
Handbook of Document Image Processing and Recognition |
Abbreviated Journal |
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| Volume |
E |
Issue |
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Pages |
749-774 |
| Keywords |
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| Abstract |
The analysis and recognition of music scores has attracted the interest of researchers for decades. Optical Music Recognition (OMR) is a classical research field of Document Image Analysis and Recognition (DIAR), whose aim is to extract information from music scores. Music scores contain both graphical and textual information, and for this reason, techniques are closely related to graphics recognition and text recognition. Since music scores use a particular diagrammatic notation that follow the rules of music theory, many approaches make use of context information to guide the recognition and solve ambiguities. This chapter overviews the main Optical Music Recognition (OMR) approaches. Firstly, the different methods are grouped according to the OMR stages, namely, staff removal, music symbol recognition, and syntactical analysis. Secondly, specific approaches for old and handwritten music scores are reviewed. Finally, online approaches and commercial systems are also commented. |
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Thesis |
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| Publisher |
Springer London |
Place of Publication |
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Editor |
D. Doermann; K. Tombre |
| 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 |
978-0-85729-860-7 |
Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
DAG; ADAS; 600.076; 600.077 |
Approved |
no |
| Call Number |
Admin @ si @ FoS2014 |
Serial |
2484 |
| Permanent link to this record |
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| Author |
Josep Llados; Marçal Rusiñol |
| Title |
Graphics Recognition Techniques |
Type |
Book Chapter |
| Year |
2014 |
Publication |
Handbook of Document Image Processing and Recognition |
Abbreviated Journal |
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| Volume |
D |
Issue |
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Pages |
489-521 |
| Keywords |
Dimension recognition; Graphics recognition; Graphic-rich documents; Polygonal approximation; Raster-to-vector conversion; Texture-based primitive extraction; Text-graphics separation |
| Abstract |
This chapter describes the most relevant approaches for the analysis of graphical documents. The graphics recognition pipeline can be splitted into three tasks. The low level or lexical task extracts the basic units composing the document. The syntactic level is focused on the structure, i.e., how graphical entities are constructed, and involves the location and classification of the symbols present in the document. The third level is a functional or semantic level, i.e., it models what the graphical symbols do and what they mean in the context where they appear. This chapter covers the lexical level, while the next two chapters are devoted to the syntactic and semantic level, respectively. The main problems reviewed in this chapter are raster-to-vector conversion (vectorization algorithms) and the separation of text and graphics components. The research and industrial communities have provided standard methods achieving reasonable performance levels. Hence, graphics recognition techniques can be considered to be in a mature state from a scientific point of view. Additionally this chapter provides insights on some related problems, namely, the extraction and recognition of dimensions in engineering drawings, and the recognition of hatched and tiled patterns. Both problems are usually associated, even integrated, in the vectorization process. |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer London |
Place of Publication |
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Editor |
D. Doermann; K. Tombre |
| Language |
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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 |
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ISBN |
978-0-85729-858-4 |
Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
DAG; 600.077 |
Approved |
no |
| Call Number |
Admin @ si @ LlR2014 |
Serial |
2380 |
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| Author |
Salvatore Tabbone; Oriol Ramos Terrades |
| Title |
An Overview of Symbol Recognition |
Type |
Book Chapter |
| Year |
2014 |
Publication |
Handbook of Document Image Processing and Recognition |
Abbreviated Journal |
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| Volume |
D |
Issue |
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Pages |
523-551 |
| Keywords |
Pattern recognition; Shape descriptors; Structural descriptors; Symbolrecognition; Symbol spotting |
| Abstract |
According to the Cambridge Dictionaries Online, a symbol is a sign, shape, or object that is used to represent something else. Symbol recognition is a subfield of general pattern recognition problems that focuses on identifying, detecting, and recognizing symbols in technical drawings, maps, or miscellaneous documents such as logos and musical scores. This chapter aims at providing the reader an overview of the different existing ways of describing and recognizing symbols and how the field has evolved to attain a certain degree of maturity. |
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Thesis |
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| Publisher |
Springer London |
Place of Publication |
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Editor |
D. Doermann; K. Tombre |
| Language |
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Summary Language |
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Original Title |
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Series Title |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-0-85729-858-4 |
Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
DAG; 600.077 |
Approved |
no |
| Call Number |
Admin @ si @ TaT2014 |
Serial |
2489 |
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| Author |
A.Kesidis; Dimosthenis Karatzas |
| Title |
Logo and Trademark Recognition |
Type |
Book Chapter |
| Year |
2014 |
Publication |
Handbook of Document Image Processing and Recognition |
Abbreviated Journal |
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| Volume |
D |
Issue |
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Pages |
591-646 |
| Keywords |
Logo recognition; Logo removal; Logo spotting; Trademark registration; Trademark retrieval systems |
| Abstract |
The importance of logos and trademarks in nowadays society is indisputable, variably seen under a positive light as a valuable service for consumers or a negative one as a catalyst of ever-increasing consumerism. This chapter discusses the technical approaches for enabling machines to work with logos, looking into the latest methodologies for logo detection, localization, representation, recognition, retrieval, and spotting in a variety of media. This analysis is presented in the context of three different applications covering the complete depth and breadth of state of the art techniques. These are trademark retrieval systems, logo recognition in document images, and logo detection and removal in images and videos. This chapter, due to the very nature of logos and trademarks, brings together various facets of document image analysis spanning graphical and textual content, while it links document image analysis to other computer vision domains, especially when it comes to the analysis of real-scene videos and images. |
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Thesis |
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| Publisher |
Springer London |
Place of Publication |
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Editor |
D. Doermann; K. Tombre |
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Original Title |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-0-85729-858-4 |
Medium |
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Expedition |
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Conference |
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| Notes |
DAG; 600.077 |
Approved |
no |
| Call Number |
Admin @ si @ KeK2014 |
Serial |
2425 |
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| Author |
Ariel Amato; Ivan Huerta; Mikhail Mozerov; Xavier Roca; Jordi Gonzalez |
| Title |
Moving Cast Shadows Detection Methods for Video Surveillance Applications |
Type |
Book Chapter |
| Year |
2014 |
Publication |
Augmented Vision and Reality |
Abbreviated Journal |
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| Volume |
6 |
Issue |
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Pages |
23-47 |
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| Abstract |
Moving cast shadows are a major concern in today’s performance from broad range of many vision-based surveillance applications because they highly difficult the object classification task. Several shadow detection methods have been reported in the literature during the last years. They are mainly divided into two domains. One usually works with static images, whereas the second one uses image sequences, namely video content. In spite of the fact that both cases can be analogously analyzed, there is a difference in the application field. The first case, shadow detection methods can be exploited in order to obtain additional geometric and semantic cues about shape and position of its casting object (‘shape from shadows’) as well as the localization of the light source. While in the second one, the main purpose is usually change detection, scene matching or surveillance (usually in a background subtraction context). Shadows can in fact modify in a negative way the shape and color of the target object and therefore affect the performance of scene analysis and interpretation in many applications. This chapter wills mainly reviews shadow detection methods as well as their taxonomies related with the second case, thus aiming at those shadows which are associated with moving objects (moving shadows). |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Series Issue |
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Edition |
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| ISSN |
2190-5916 |
ISBN |
978-3-642-37840-9 |
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| Notes |
ISE; 605.203; 600.049; 302.018; 302.012; 600.078 |
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no |
| Call Number |
Admin @ si @ AHM2014 |
Serial |
2223 |
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| Author |
Josep Llados; Gemma Sanchez; Enric Marti |
| Title |
A string based method to recognize symbols and structural textures in architectural plans |
Type |
Book Chapter |
| Year |
1998 |
Publication |
Graphics Recognition Algorithms and Systems Second International Workshop, GREC' 97 Nancy, France, August 22–23, 1997 Selected Papers |
Abbreviated Journal |
LNCS |
| Volume |
1389 |
Issue |
1998 |
Pages |
91-103 |
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| Abstract |
This paper deals with the recognition of symbols and structural textures in architectural plans using string matching techniques. A plan is represented by an attributed graph whose nodes represent characteristic points and whose edges represent segments. Symbols and textures can be seen as a set of regions, i.e. closed loops in the graph, with a particular arrangement. The search for a symbol involves a graph matching between the regions of a model graph and the regions of the graph representing the document. Discriminating a texture means a clustering of neighbouring regions of this graph. Both procedures involve a similarity measure between graph regions. A string codification is used to represent the sequence of outlining edges of a region. Thus, the similarity between two regions is defined in terms of the string edit distance between their boundary strings. The use of string matching allows the recognition method to work also under presence of distortion. |
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Springer Link |
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LNCS |
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DAG; IAM |
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no |
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IAM @ iam @ SLE1998 |
Serial |
1573 |
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| Author |
Ole Larsen; Petia Radeva; Enric Marti |
| Title |
Bounds on the optimal elasticity parameters for a snake |
Type |
Journal Article |
| Year |
1995 |
Publication |
Image Analysis and Processing |
Abbreviated Journal |
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Issue |
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Pages |
37-42 |
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| Abstract |
This paper develops a formalism by which an estimate for the upper and lower bounds for the elasticity parameters for a snake can be obtained. Objects different in size and shape give rise to different bounds. The bounds can be obtained based on an analysis of the shape of the object of interest. Experiments on synthetic images show a good correlation between the estimated behaviour of the snake and the one actually observed. Experiments on real X-ray images show that the parameters for optimal segmentation lie within the estimated bounds. |
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MILAB;IAM |
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no |
| Call Number |
IAM @ iam @ LRM1995a |
Serial |
1559 |
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| Author |
Petia Radeva; Enric Marti |
| Title |
An improved model of snakes for model-based segmentation |
Type |
Conference Article |
| Year |
1995 |
Publication |
Proceedings of Computer Analysis of Images and Patterns |
Abbreviated Journal |
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Issue |
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Pages |
515-520 |
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| Abstract |
The main advantage of segmentation by snakes consists in its ability to incorporate smoothness constraints on the detected shapes that can occur. Likewise, we propose to model snakes with other properties that reflect the information provided about the object of interest in a different extent. We consider different kinds of snakes, those searching for contours with a certain direction, those preserving an object’s model, those seeking for symmetry, those expanding open, etc. The availability of such a collection of snakes allows not only the more complete use of the knowledge about the segmented object, but also to solve some problems of the existing snakes. Our experiments on segmentation of facial features justify the usefulness of snakes with different properties. |
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Conference |
CAIP |
| Notes |
MILAB;IAM |
Approved |
no |
| Call Number |
IAM @ iam @ RaM1995b |
Serial |
1632 |
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| Author |
Ole Vilhelm-Larsen; Petia Radeva; Enric Marti |
| Title |
Guidelines for choosing optimal parameters of elasticity for snakes |
Type |
Book Chapter |
| Year |
1995 |
Publication |
Computer Analysis Of Images And Patterns |
Abbreviated Journal |
LNCS |
| Volume |
970 |
Issue |
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Pages |
106-113 |
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| Abstract |
This paper proposes a guidance in the process of choosing and using the parameters of elasticity of a snake in order to obtain a precise segmentation. A new two step procedure is defined based on upper and lower bounds on the parameters. Formulas, by which these bounds can be calculated for real images where parts of the contour may be missing, are presented. Experiments on segmentation of bone structures in X-ray images have verified the usefulness of the new procedure. |
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Lecture Notes in Computer Science |
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LNCS |
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| Notes |
MILAB;IAM |
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no |
| Call Number |
IAM @ iam @ LRM1995b |
Serial |
1558 |
| Permanent link to this record |
