| Records |
Author  |
Jose Antonio Rodriguez; Florent Perronnin |
| Title |
Local Gradient Histogram Features for Word Spotting in Unconstrained Handwritten Documents |
Type |
Book Chapter |
| Year |
2008 |
Publication |
Graphics Recognition: Recent Advances and New Opportunities |
Abbreviated Journal |
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| Volume |
5046 |
Issue |
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Pages |
188–198 |
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Editor |
W. Liu, J. Llados, J.M. Ogier |
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LNCS |
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no |
| Call Number |
Admin @ si @ RoP2008a |
Serial |
992 |
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| Author |
Jose Antonio Rodriguez; Gemma Sanchez; Josep Llados |
| Title |
Rejection strategies involving classifier combination for handwriting recognition |
Type |
Book Chapter |
| Year |
2007 |
Publication |
3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4478:97–104 |
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Girona (Spain) |
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DAG |
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no |
| Call Number |
DAG @ dag @ RSL2007a |
Serial |
777 |
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| Author |
Jose Antonio Rodriguez; Gemma Sanchez; Josep Llados |
| Title |
Categorization of Digital Ink Elements using Spectral Features |
Type |
Book Chapter |
| Year |
2008 |
Publication |
Graphics Recognition: Recent Advances and New Opportunities |
Abbreviated Journal |
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| Volume |
5046 |
Issue |
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Pages |
188–198 |
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| Publisher |
Springer–Verlag |
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Editor |
W. Liu, J. Llados, J.M. Ogier |
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LNCS |
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DAG |
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no |
| Call Number |
DAG @ dag @ RSL2008 |
Serial |
1099 |
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| Author |
Jose M. Armingol; Jorge Alfonso; Nourdine Aliane; Miguel Clavijo; Sergio Campos-Cordobes; Arturo de la Escalera; Javier del Ser; Javier Fernandez; Fernando Garcia; Felipe Jimenez; Antonio Lopez; Mario Mata |
| Title |
Environmental Perception for Intelligent Vehicles |
Type |
Book Chapter |
| Year |
2018 |
Publication |
Intelligent Vehicles. Enabling Technologies and Future Developments |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
23–101 |
| Keywords |
Computer vision; laser techniques; data fusion; advanced driver assistance systems; traffic monitoring systems; intelligent vehicles |
| Abstract |
Environmental perception represents, because of its complexity, a challenge for Intelligent Transport Systems due to the great variety of situations and different elements that can happen in road environments and that must be faced by these systems. In connection with this, so far there are a variety of solutions as regards sensors and methods, so the results of precision, complexity, cost, or computational load obtained by these works are different. In this chapter some systems based on computer vision and laser techniques are presented. Fusion methods are also introduced in order to provide advanced and reliable perception systems. |
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ADAS; 600.118 |
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no |
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Admin @ si @AAA2018 |
Serial |
3046 |
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| Author |
Jose Manuel Alvarez; Antonio Lopez |
| Title |
Photometric Invariance by Machine Learning |
Type |
Book Chapter |
| Year |
2012 |
Publication |
Color in Computer Vision: Fundamentals and Applications |
Abbreviated Journal |
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| Volume |
7 |
Issue |
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Pages |
113-134 |
| Keywords |
road detection |
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| Publisher |
iConcept Press Ltd |
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Editor |
Theo Gevers, Arjan Gijsenij, Joost van de Weijer, Jan-Mark Geusebroek |
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ISBN |
978-0-470-89084-4 |
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ADAS |
Approved |
no |
| Call Number |
Admin @ si @ AlL2012 |
Serial |
2186 |
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| Author |
Josep Llados |
| Title |
Advances in Graphics Recognition |
Type |
Book Chapter |
| Year |
2007 |
Publication |
Digital Document Processing, Major Directions and Recent Advances, Advances in Pattern Recognition, B.B. Chaudhuri, ed., 281–304 |
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Springer London |
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DAG |
Approved |
no |
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DAG @ dag @ Lla2007 |
Serial |
780 |
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| Author |
Josep Llados; Ernest Valveny; Enric Marti |
| Title |
Symbol Recognition in Document Image Analysis: Methods and Challenges |
Type |
Book Chapter |
| Year |
2000 |
Publication |
Recent Research Developments in Pattern Recognition, Transworld Research Network, |
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| Volume |
1 |
Issue |
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Pages |
151–178. |
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ISBN |
81-86846-61-1 |
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| Notes |
DAG;IAM |
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no |
| Call Number |
IAM @ iam @ LVM2000 |
Serial |
1575 |
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| Author |
Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti |
| Title |
Symbol recognition: current advances and perspectives |
Type |
Book Chapter |
| Year |
2002 |
Publication |
Graphics Recognition Algorithms And Applications |
Abbreviated Journal |
LNCS |
| Volume |
2390 |
Issue |
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Pages |
104-128 |
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| Abstract |
The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content. |
| Address |
London, UK |
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Springer-Verlag |
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Editor |
Dorothea Blostein and Young- Bin Kwon |
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Lecture Notes in Computer Science |
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LNCS |
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ISBN |
3-540-44066-6 |
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Conference |
GREC |
| Notes |
DAG; IAM; |
Approved |
no |
| Call Number |
IAM @ iam @ LVS2002 |
Serial |
1572 |
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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 |
| Call Number |
IAM @ iam @ SLE1998 |
Serial |
1573 |
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| Author |
Josep Llados; Jaime Lopez-Krahe; Enric Marti |
| Title |
A system to understand hand-drawn floor plans using subgraph isomorphism and Hough transform |
Type |
Book Chapter |
| Year |
1997 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
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| Volume |
10 |
Issue |
3 |
Pages |
150-158 |
| Keywords |
Line drawings – Hough transform – Graph matching – CAD systems – Graphics recognition |
| Abstract |
Presently, man-machine interface development is a widespread research activity. A system to understand hand drawn architectural drawings in a CAD environment is presented in this paper. To understand a document, we have to identify its building elements and their structural properties. An attributed graph structure is chosen as a symbolic representation of the input document and the patterns to recognize in it. An inexact subgraph isomorphism procedure using relaxation labeling techniques is performed. In this paper we focus on how to speed up the matching. There is a building element, the walls, characterized by a hatching pattern. Using a straight line Hough transform (SLHT)-based method, we recognize this pattern, characterized by parallel straight lines, and remove from the input graph the edges belonging to this pattern. The isomorphism is then applied to the remainder of the input graph. When all the building elements have been recognized, the document is redrawn, correcting the inaccurate strokes obtained from a hand-drawn input. |
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DAG;IAM |
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no |
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IAM @ iam @ LLM1997a |
Serial |
1566 |
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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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Springer London |
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Editor |
D. Doermann; K. Tombre |
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ISBN |
978-0-85729-858-4 |
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DAG; 600.077 |
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no |
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Admin @ si @ LlR2014 |
Serial |
2380 |
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| Author |
Josep Llados; Partha Pratim Roy; Jose Antonio Rodriguez; Gemma Sanchez |
| Title |
Word Spotting in Archive Documents using Shape Contexts |
Type |
Book Chapter |
| Year |
2007 |
Publication |
3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4478:290–297 |
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Girona (Spain) |
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DAG |
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no |
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DAG @ dag @ LRR2007 |
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779 |
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| Author |
Juan Andrade; T. Alejandra Vidal; A. Sanfeliu |
| Title |
Stochastic state estimation for simultaneous localization and map building in mobile robotics |
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Book Chapter |
| Year |
2005 |
Publication |
Vedran Kordic, Aleksandar Lazinica, and Munir Merdan (Eds.), Cutting Edge Robotics, Advanced Robotic Systems Press, 3.3:223–242 |
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Admin @ si @ AVS2005a |
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565 |
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| Author |
Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu |
| Title |
Robust Head Gestures Recognition for Assistive Technology |
Type |
Book Chapter |
| Year |
2014 |
Publication |
Pattern Recognition |
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| Volume |
8495 |
Issue |
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Pages |
152-161 |
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| Abstract |
This paper presents a system capable of recognizing six head gestures: nodding, shaking, turning right, turning left, looking up, and looking down. The main difference of our system compared to other methods is that the Hidden Markov Models presented in this paper, are fully connected and consider all possible states in any given order, providing the following advantages to the system: (1) allows unconstrained movement of the head and (2) it can be easily integrated into a wearable device (e.g. glasses, neck-hung devices), in which case it can robustly recognize gestures in the presence of ego-motion. Experimental results show that this approach outperforms common methods that use restricted HMMs for each gesture. |
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Springer International Publishing |
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LNCS |
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0302-9743 |
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978-3-319-07490-0 |
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LAMP; |
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no |
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Admin @ si @ TSR2014b |
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2505 |
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| Author |
Julie Digne; Mariella Dimiccoli; Neus Sabater; Philippe Salembier |
| Title |
Neighborhood Filters and the Recovery of 3D Information |
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Book Chapter |
| Year |
2015 |
Publication |
Handbook of Mathematical Methods in Imaging |
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Issue |
III |
Pages |
1645-1673 |
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| Abstract |
Following their success in image processing (see Chapter Local Smoothing Neighborhood Filters), neighborhood filters have been extended to 3D surface processing. This adaptation is not straightforward. It has led to several variants for surfaces depending on whether the surface is defined as a mesh, or as a raw data point set. The image gray level in the bilateral similarity measure is replaced by a geometric information such as the normal or the curvature. The first section of this chapter reviews the variants of 3D mesh bilateral filters and compares them to the simplest possible isotropic filter, the mean curvature motion.In a second part, this chapter reviews applications of the bilateral filter to a data composed of a sparse depth map (or of depth cues) and of the image on which they have been computed. Such sparse depth cues can be obtained by stereovision or by psychophysical techniques. The underlying assumption to these applications is that pixels with similar intensity around a region are likely to have similar depths. Therefore, when diffusing depth information with a bilateral filter based on locality and color similarity, the discontinuities in depth are assured to be consistent with the color discontinuities, which is generally a desirable property. In the reviewed applications, this ends up with the reconstruction of a dense perceptual depth map from the joint data of an image and of depth cues. |
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Springer New York |
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978-1-4939-0789-2 |
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MILAB |
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no |
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Admin @ si @ DDS2015 |
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2710 |
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