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Author |
Sergio Escalera; Oriol Pujol; Eric Laciar; Jordi Vitria; Esther Pueyo; Petia Radeva |
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Title |
Classification of Coronary Damage in Chronic Chagasic Patients |
Type |
Book Chapter |
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Year |
2010 |
Publication |
Intelligent Systems – From Theory to Practice. Studies in Computational Intelligence |
Abbreviated Journal |
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Volume |
299 |
Issue |
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Pages |
461-478 |
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Keywords |
Chagas disease; Error-Correcting Output Codes; High resolution ECG; Decoding |
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Abstract |
Post Conference IEEE-IS 2008
The Chagas’ disease is endemic in all Latin America, affecting millions of people in the continent. In order to diagnose and treat the chagas’ disease, it is important to detect and measure the coronary damage of the patient. In this paper,
we analyze and categorize patients into different groups based on the coronary damage produced by the disease. Based on the features of the heart cycle extracted using high resolution ECG, a multi-class scheme of Error-Correcting Output Codes (ECOC)is formulated and successfully applied. The results show that the proposed scheme obtains significant performance improvements compared to previous works and state-of-the-art ECOC designs. |
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Springer-Verlag |
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V. Sgurev, M. Hadjiski (eds) |
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OR;MILAB;HUPBA;MV |
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BCNPCL @ bcnpcl @ EPL2010 |
Serial |
1452 |
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Author |
Francesco Ciompi; Oriol Pujol; E Fernandez-Nofrerias; J. Mauri; Petia Radeva |
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Title |
Conditional Random Fields for image segmentation in Intravascular Ultrasound |
Type |
Conference Article |
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Year |
2010 |
Publication |
Medical Image Computing in Catalunya: Graduate Student Workshop |
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Pages |
13–14 |
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We present a Conditional Random Fields based approach for segmenting Intravascular Ultrasond (IVUS) images. The presented method uses a contextual discriminative graphical model to deal with the presence of distorsions and artifacts in IVUS images, that turns the segmentation of interesting regions into a difficult task. An accurate lumen segmentation on IVUS longitudinal images is achieved. |
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Girona |
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MICCAT |
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MILAB;HUPBA |
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no |
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Call Number |
BCNPCL @ bcnpcl @ CPF2010 |
Serial |
1453 |
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Author |
Jose Manuel Alvarez |
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Title |
Combining Context and Appearance for Road Detection |
Type |
Book Whole |
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Year |
2010 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Road traffic crashes have become a major cause of death and injury throughout the world.
Hence, in order to improve road safety, the automobile manufacture is moving towards the
development of vehicles with autonomous functionalities such as keeping in the right lane, safe distance keeping between vehicles or regulating the speed of the vehicle according to the traffic conditions. A key component of these systems is vision–based road detection that aims to detect the free road surface ahead the moving vehicle. Detecting the road using a monocular vision system is very challenging since the road is an outdoor scenario imaged from a mobile platform. Hence, the detection algorithm must be able to deal with continuously changing imaging conditions such as the presence ofdifferent objects (vehicles, pedestrians), different environments (urban, highways, off–road), different road types (shape, color), and different imaging conditions (varying illumination, different viewpoints and changing weather conditions). Therefore, in this thesis, we focus on vision–based road detection using a single color camera. More precisely, we first focus on analyzing and grouping pixels according to their low–level properties. In this way, two different approaches are presented to exploit
color and photometric invariance. Then, we focus the research of the thesis on exploiting context information. This information provides relevant knowledge about the road not using pixel features from road regions but semantic information from the analysis of the scene.
In this way, we present two different approaches to infer the geometry of the road ahead
the moving vehicle. Finally, we focus on combining these context and appearance (color)
approaches to improve the overall performance of road detection algorithms. The qualitative and quantitative results presented in this thesis on real–world driving sequences show that the proposed method is robust to varying imaging conditions, road types and scenarios going beyond the state–of–the–art. |
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Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Editor |
Antonio Lopez;Theo Gevers |
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978-84-937261-8-8 |
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ADAS |
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no |
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Call Number |
Admin @ si @ Alv2010 |
Serial |
1454 |
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Author |
Partha Pratim Roy |
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Title |
Multi-Oriented and Multi-Scaled Text Character Analysis and Recognition in Graphical Documents and their Applications to Document Image Retrieval |
Type |
Book Whole |
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Year |
2010 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
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With the advent research of Document Image Analysis and Recognition (DIAR), an
important line of research is explored on indexing and retrieval of graphics rich documents. It aims at finding relevant documents relying on segmentation and recognition
of text and graphics components underlying in non-standard layout where commercial
OCRs can not be applied due to complexity. This thesis is focused towards text information extraction approaches in graphical documents and retrieval of such documents
using text information.
Automatic text recognition in graphical documents (map, engineering drawing,
etc.) involves many challenges because text characters are usually printed in multioriented and multi-scale way along with different graphical objects. Text characters
are used to annotate the graphical curve lines and hence, many times they follow
curvi-linear paths too. For OCR of such documents, individual text lines and their
corresponding words/characters need to be extracted.
For recognition of multi-font, multi-scale and multi-oriented characters, we have
proposed a feature descriptor for character shape using angular information from contour pixels to take care of the invariance nature. To improve the efficiency of OCR, an
approach towards the segmentation of multi-oriented touching strings into individual
characters is also discussed. Convex hull based background information is used to
segment a touching string into possible primitive segments and later these primitive
segments are merged to get optimum segmentation using dynamic programming. To
overcome the touching/overlapping problem of text with graphical lines, a character
spotting approach using SIFT and skeleton information is included. Afterwards, we
propose a novel method to extract individual curvi-linear text lines using the foreground and background information of the characters of the text and a water reservoir
concept is used to utilize the background information.
We have also formulated the methodologies for graphical document retrieval applications using query words and seals. The retrieval approaches are performed using
recognition results of individual components in the document. Given a query text,
the system extracts positional knowledge from the query word and uses the same to
generate hypothetical locations in the document. Indexing of documents is also performed based on automatic detection of seals from documents containing cluttered
background. A seal is characterized by scale and rotation invariant spatial feature
descriptors computed from labelled text characters and a concept based on the Generalized Hough Transform is used to locate the seal in documents. |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Editor |
Josep Llados;Umapada Pal |
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978-84-937261-7-1 |
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no |
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Call Number |
Admin @ si @ Roy2010 |
Serial |
1455 |
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Author |
Jose Manuel Alvarez; Antonio Lopez |
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Title |
Road Detection Based on Illuminant Invariance |
Type |
Journal Article |
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Year |
2011 |
Publication |
IEEE Transactions on Intelligent Transportation Systems |
Abbreviated Journal |
TITS |
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Volume |
12 |
Issue |
1 |
Pages |
184-193 |
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Keywords |
road detection |
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Abstract |
By using an onboard camera, it is possible to detect the free road surface ahead of the ego-vehicle. Road detection is of high relevance for autonomous driving, road departure warning, and supporting driver-assistance systems such as vehicle and pedestrian detection. The key for vision-based road detection is the ability to classify image pixels as belonging or not to the road surface. Identifying road pixels is a major challenge due to the intraclass variability caused by lighting conditions. A particularly difficult scenario appears when the road surface has both shadowed and nonshadowed areas. Accordingly, we propose a novel approach to vision-based road detection that is robust to shadows. The novelty of our approach relies on using a shadow-invariant feature space combined with a model-based classifier. The model is built online to improve the adaptability of the algorithm to the current lighting and the presence of other vehicles in the scene. The proposed algorithm works in still images and does not depend on either road shape or temporal restrictions. Quantitative and qualitative experiments on real-world road sequences with heavy traffic and shadows show that the method is robust to shadows and lighting variations. Moreover, the proposed method provides the highest performance when compared with hue-saturation-intensity (HSI)-based algorithms. |
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ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ AlL2011 |
Serial |
1456 |
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Author |
Cesar Isaza; Joaquin Salas; Bogdan Raducanu |
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Title |
Toward the Detection of Urban Infrastructures Edge Shadows |
Type |
Conference Article |
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Year |
2010 |
Publication |
12th International Conference on Advanced Concepts for Intelligent Vision Systems |
Abbreviated Journal |
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Volume |
6474 |
Issue |
I |
Pages |
30–37 |
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Abstract |
In this paper, we propose a novel technique to detect the shadows cast by urban infrastructure, such as buildings, billboards, and traffic signs, using a sequence of images taken from a fixed camera. In our approach, we compute two different background models in parallel: one for the edges and one for the reflected light intensity. An algorithm is proposed to train the system to distinguish between moving edges in general and edges that belong to static objects, creating an edge background model. Then, during operation, a background intensity model allow us to separate between moving and static objects. Those edges included in the moving objects and those that belong to the edge background model are subtracted from the current image edges. The remaining edges are the ones cast by urban infrastructure. Our method is tested on a typical crossroad scene and the results show that the approach is sound and promising. |
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Sydney, Australia |
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Springer Berlin Heidelberg |
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Editor |
eds. Blanc–Talon et al |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-17687-6 |
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Conference |
ACIVS |
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Notes |
OR;MV |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ ISR2010 |
Serial |
1458 |
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Author |
Muhammad Muzzamil Luqman; Josep Llados; Jean-Yves Ramel; Thierry Brouard |
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Title |
A Fuzzy-Interval Based Approach For Explicit Graph Embedding, Recognizing Patterns in Signals, Speech, Images and Video |
Type |
Conference Article |
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Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
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Volume |
6388 |
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Pages |
93–98 |
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Abstract |
We present a new method for explicit graph embedding. Our algorithm extracts a feature vector for an undirected attributed graph. The proposed feature vector encodes details about the number of nodes, number of edges, node degrees, the attributes of nodes and the attributes of edges in the graph. The first two features are for the number of nodes and the number of edges. These are followed by w features for node degrees, m features for k node attributes and n features for l edge attributes — which represent the distribution of node degrees, node attribute values and edge attribute values, and are obtained by defining (in an unsupervised fashion), fuzzy-intervals over the list of node degrees, node attributes and edge attributes. Experimental results are provided for sample data of ICPR2010 contest GEPR. |
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Springer, Heidelberg |
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0302-9743 |
ISBN |
978-3-642-17710-1 |
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ICPR |
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DAG |
Approved |
no |
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Call Number |
DAG @ dag @ LLR2010 |
Serial |
1459 |
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Author |
Muhammad Muzzamil Luqman; Thierry Brouard; Jean-Yves Ramel; Josep Llados |
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Title |
A Content Spotting System For Line Drawing Graphic Document Images |
Type |
Conference Article |
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Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
Abbreviated Journal |
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Volume |
20 |
Issue |
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Pages |
3420–3423 |
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Abstract |
We present a content spotting system for line drawing graphic document images. The proposed system is sufficiently domain independent and takes the keyword based information retrieval for graphic documents, one step forward, to Query By Example (QBE) and focused retrieval. During offline learning mode: we vectorize the documents in the repository, represent them by attributed relational graphs, extract regions of interest (ROIs) from them, convert each ROI to a fuzzy structural signature, cluster similar signatures to form ROI classes and build an index for the repository. During online querying mode: a Bayesian network classifier recognizes the ROIs in the query image and the corresponding documents are fetched by looking up in the repository index. Experimental results are presented for synthetic images of architectural and electronic documents. |
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1051-4651 |
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978-1-4244-7542-1 |
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ICPR |
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DAG |
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DAG @ dag @ LBR2010b |
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1460 |
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Author |
Thierry Brouard; A. Delaplace; Muhammad Muzzamil Luqman; H. Cardot; Jean-Yves Ramel |
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Title |
Design of Evolutionary Methods Applied to the Learning of Bayesian Nerwork Structures |
Type |
Book Chapter |
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Year |
2010 |
Publication |
Bayesian Network |
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13-37 |
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Sciyo |
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Editor |
Ahmed Rebai |
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978-953-307-124-4 |
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Admin @ si @ BDL2010 |
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1461 |
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Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
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Title |
Graph of Words Embedding for Molecular Structure-Activity Relationship Analysis |
Type |
Conference Article |
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Year |
2010 |
Publication |
15th Iberoamerican Congress on Pattern Recognition |
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6419 |
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30–37 |
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Abstract |
Structure-Activity relationship analysis aims at discovering chemical activity of molecular compounds based on their structure. In this article we make use of a particular graph representation of molecules and propose a new graph embedding procedure to solve the problem of structure-activity relationship analysis. The embedding is essentially an arrangement of a molecule in the form of a vector by considering frequencies of appearing atoms and frequencies of covalent bonds between them. Results on two benchmark databases show the effectiveness of the proposed technique in terms of recognition accuracy while avoiding high operational costs in the transformation. |
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Sao Paulo, Brazil |
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LNCS |
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0302-9743 |
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978-3-642-16686-0 |
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CIARP |
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DAG |
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DAG @ dag @ GVB2010 |
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1462 |
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Author |
Ariel Amato; Mikhail Mozerov; Xavier Roca; Jordi Gonzalez |
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Title |
Robust Real-Time Background Subtraction Based on Local Neighborhood Patterns |
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Journal Article |
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Year |
2010 |
Publication |
EURASIP Journal on Advances in Signal Processing |
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EURASIPJ |
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7 |
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Abstract |
Article ID 901205
This paper describes an efficient background subtraction technique for detecting moving objects. The proposed approach is able to overcome difficulties like illumination changes and moving shadows. Our method introduces two discriminative features based on angular and modular patterns, which are formed by similarity measurement between two sets of RGB color vectors: one belonging to the background image and the other to the current image. We show how these patterns are used to improve foreground detection in the presence of moving shadows and in the case when there are strong similarities in color between background and foreground pixels. Experimental results over a collection of public and own datasets of real image sequences demonstrate that the proposed technique achieves a superior performance compared with state-of-the-art methods. Furthermore, both the low computational and space complexities make the presented algorithm feasible for real-time applications. |
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1110-8657 |
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ISE |
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ISE @ ise @ AMR2010 |
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1463 |
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Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Title |
Embedding Random Projections in Regularized Gradient Boosting Machines |
Type |
Conference Article |
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Year |
2010 |
Publication |
Supervised and Unsupervised Ensemble Methods and their Applications in the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases |
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44–53 |
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Barcelona (Spain) |
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SUEMA |
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MILAB;HUPBA |
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no |
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BCNPCL @ bcnpcl @ CPR2010c |
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1466 |
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Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Title |
Classyfing Agitation in Sedated ICU Patients |
Type |
Conference Article |
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Year |
2010 |
Publication |
Medical Image Computing in Catalunya: Graduate Student Workshop |
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Pages |
19–20 |
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Agitation is a serious problem in sedated intensive care unit (ICU) patients. In this work, standard machine learning techniques working on wearable accelerometer data have been used to classifying agitation levels achieving very good classification performances. |
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Girona |
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MICCAT |
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MILAB;HUPBA |
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no |
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Call Number |
BCNPCL @ bcnpcl @ COR2010 |
Serial |
1467 |
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Author |
Angel Sappa (ed) |
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Title |
Computer Graphics and Imaging |
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Book Whole |
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Year |
2010 |
Publication |
Computer Graphics and Imaging |
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Angel Sappa |
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978–0–88986–836–6 |
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CGIM |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ Sap2010 |
Serial |
1468 |
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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Title |
Reduction of Pattern Search Area in Colonoscopy Images by Merging Non-Informative Regions |
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Conference Article |
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Year |
2010 |
Publication |
28th Congreso Anual de la Sociedad Española de Ingeniería Biomédica |
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Abstract |
One of the first usual steps in pattern recognition schemas is image segmentation, in order to reduce the dimensionality of the problem and manage smaller quantity of data. In our case as we are pursuing real-time colon cancer polyp detection, this step is crucial. In this paper we present a non-informative region estimation algorithm that will let us discard some parts of the image where we will not expect to find colon cancer polyps. The performance of our approach will be measured in terms of both non-informative areas elimination and polyps’ areas preserving. The results obtained show the importance of having correct non- informative region estimation in order to fasten the whole recognition process. |
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Madrid (Spain) |
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800 |
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CASEIB |
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Notes |
MV;SIAI |
Approved |
no |
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Call Number |
Admin @ si @ BSV2010 |
Serial |
1469 |
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| Permanent link to this record |
