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Author | F.Guirado; Ana Ripoll; C.Roig; Aura Hernandez-Sabate; Emilio Luque | ||||
Title | Exploiting Throughput for Pipeline Execution in Streaming Image Processing Applications | Type | Book Chapter | ||
Year | 2006 | Publication | Euro-Par 2006 Parallel Processing | Abbreviated Journal | LNCS |
Volume | 4128 | Issue | Pages | 1095-1105 | |
Keywords | 12th International Euro–Par Conference | ||||
Abstract | There is a large range of image processing applications that act on an input sequence of image frames that are continuously received. Throughput is a key performance measure to be optimized when execu- ting them. In this paper we propose a new task replication methodology for optimizing throughput for an image processing application in the field of medicine. The results show that by applying the proposed methodo- logy we are able to achieve the desired throughput in all cases, in such a way that the input frames can be processed at any given rate. | ||||
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Publisher | Springer-Verlag Berlin Heidelberg | Place of Publication | Dresden, Germany (European Union) | Editor | UAB; W, E.N.; et al. |
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Series Editor | Series Title | Lecture Notes In Computer Science | Abbreviated Series Title | ||
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Area | Expedition | Conference | Euro–Par | ||
Notes | IAM | Approved | no | ||
Call Number | IAM @ iam @ GRR2006a | Serial | 1542 | ||
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Author | Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva | ||||
Title | On the Design of Low Redundancy Error-Correcting Output Codes | Type | Book Chapter | ||
Year | 2011 | Publication | Ensembles in Machine Learning Applications | Abbreviated Journal | |
Volume | 373 | Issue | 2 | Pages | 21-38 |
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Abstract | The classification of large number of object categories is a challenging trend in the Pattern Recognition field. In the literature, this is often addressed using an ensemble of classifiers . In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for combining classifiers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classifiers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a compact design of ECOC in terms of the number of classifiers. Evolutionary computation is used for tuning the parameters of the classifiers and looking for the best compact ECOC code configuration. The results over several public UCI data sets and different multi-class Computer Vision problems show that the proposed methodology obtains comparable (even better) results than the state-of-the-art ECOC methodologies with far less number of dichotomizers. | ||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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ISSN | 1860-949X | ISBN | 978-3-642-22909-1 | Medium | |
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Notes | MILAB; OR;HuPBA;MV | Approved | no | ||
Call Number | Admin @ si @ BEB2011b | Serial | 1886 | ||
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Author | Debora Gil; Petia Radeva | ||||
Title | Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling | Type | Book Chapter | ||
Year | 2003 | Publication | Energy Minimization Methods In Computer Vision And Pattern Recognition | Abbreviated Journal | LNCS |
Volume | 2683 | Issue | Pages | 357-372 | |
Keywords | Initial condition; Convex shape; Non convex analysis; Increase; Segmentation; Gradient; Standard; Standards; Concave shape; Flow models; Tracking; Edge detection; Curvature | ||||
Abstract | Poor convergence to concave shapes is a main limitation of snakes as a standard segmentation and shape modelling technique. The gradient of the external energy of the snake represents a force that pushes the snake into concave regions, as its internal energy increases when new inexion points are created. In spite of the improvement of the external energy by the gradient vector ow technique, highly non convex shapes can not be obtained, yet. In the present paper, we develop a new external energy based on the geometry of the curve to be modelled. By tracking back the deformation of a curve that evolves by minimum curvature ow, we construct a distance map that encapsulates the natural way of adapting to non convex shapes. The gradient of this map, which we call curvature vector ow (CVF), is capable of attracting a snake towards any contour, whatever its geometry. Our experiments show that, any initial snake condition converges to the curve to be modelled in optimal time. | ||||
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Publisher | Springer, Berlin | Place of Publication | Lisbon, PORTUGAL | Editor | Springer, B. |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Lecture Notes in Computer Science | Abbreviated Series Title | LNCS | |
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 3-540-40498-8 | Medium | |
Area | Expedition | Conference | |||
Notes | IAM;MILAB | Approved | no | ||
Call Number | IAM @ iam @ GIR2003b | Serial | 1535 | ||
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Author | Angel Sappa; Niki Aifanti; Sotiris Malassiotis; N. Grammalidis | ||||
Title | Survey of 3D Human Body Representations | Type | Book Chapter | ||
Year | 2005 | Publication | Encyclopedia of Information Science and Technology, 1(5):2696–2701 | Abbreviated Journal | |
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Notes | Approved | no | |||
Call Number | ADAS @ adas @ SAM2005a | Serial | 497 | ||
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Author | Niki Aifanti; Angel Sappa; N. Grammalidis; Sotiris Malassiotis | ||||
Title | Human Motion Tracking and Recognition | Type | Book Chapter | ||
Year | 2005 | Publication | Encyclopedia of Information Science and Technology, 1(5):1355–1360 | Abbreviated Journal | |
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Notes | Approved | no | |||
Call Number | ADAS @ adas @ ASG2005 | Serial | 496 | ||
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Author | Niki Aifanti; Angel Sappa; N. Grammalidis; Sotiris Malassiotis | ||||
Title | Advances in Tracking and Recognition of Human Motion | Type | Book Chapter | ||
Year | 2009 | Publication | Encyclopedia of Information Science and Technology | Abbreviated Journal | |
Volume | I | Issue | 2nd edition | Pages | 65–71 |
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Notes | ADAS | Approved | no | ||
Call Number | ADAS @ adas @ ASG2009 | Serial | 1143 | ||
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Author | C. Alejandro Parraga | ||||
Title | Color Vision, Computational Methods for | Type | Book Chapter | ||
Year | 2014 | Publication | Encyclopedia of Computational Neuroscience | Abbreviated Journal | |
Volume | Issue | 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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Publisher | Springer-Verlag Berlin Heidelberg | Place of Publication | Editor | Dieter Jaeger; Ranu Jung | |
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ISSN | ISBN | 978-1-4614-7320-6 | Medium | ||
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Notes | CIC; 600.074 | Approved | no | ||
Call Number | Admin @ si @ Par2014 | Serial | 2512 | ||
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Author | Fadi Dornaika; Bogdan Raducanu | ||||
Title | Facial Expression Recognition for HCI Applications | Type | Book Chapter | ||
Year | 2008 | Publication | Encyclopedia of Artificial Intelligence | Abbreviated Journal | |
Volume | II | Issue | Pages | 625–631 | |
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Publisher | IGI–Global Publisher | Place of Publication | Editor | Rabuñal | |
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Notes | OR;MV | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ DoR2008c | Serial | 1034 | ||
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Author | Fadi Dornaika; Bogdan Raducanu; Alireza Bosaghzadeh | ||||
Title | Facial expression recognition based on multi observations with application to social robotics | Type | Book Chapter | ||
Year | 2015 | Publication | Emotional and Facial Expressions: Recognition, Developmental Differences and Social Importance | Abbreviated Journal | |
Volume | Issue | Pages | 153-166 | ||
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Abstract | Human-robot interaction is a hot topic nowadays in the social robotics
community. One crucial aspect is represented by the affective communication which comes encoded through the facial expressions. In this chapter, we propose a novel approach for facial expression recognition, which exploits an efficient and adaptive graph-based label propagation (semi-supervised mode) in a multi-observation framework. The facial features are extracted using an appearance-based 3D face tracker, viewand texture independent. Our method has been extensively tested on the CMU dataset, and has been conveniently compared with other methods for graph construction. With the proposed approach, we developed an application for an AIBO robot, in which it mirrors the recognized facial expression. |
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Publisher | Nova Science publishers | Place of Publication | Editor | Bruce Flores | |
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Notes | LAMP; | Approved | no | ||
Call Number | Admin @ si @ DRB2015 | Serial | 2720 | ||
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Author | Antonio Lopez; Jiaolong Xu; Jose Luis Gomez; David Vazquez; German Ros | ||||
Title | From Virtual to Real World Visual Perception using Domain Adaptation -- The DPM as Example | Type | Book Chapter | ||
Year | 2017 | Publication | Domain Adaptation in Computer Vision Applications | Abbreviated Journal | |
Volume | Issue | 13 | Pages | 243-258 | |
Keywords | Domain Adaptation | ||||
Abstract | Supervised learning tends to produce more accurate classifiers than unsupervised learning in general. This implies that training data is preferred with annotations. When addressing visual perception challenges, such as localizing certain object classes within an image, the learning of the involved classifiers turns out to be a practical bottleneck. The reason is that, at least, we have to frame object examples with bounding boxes in thousands of images. A priori, the more complex the model is regarding its number of parameters, the more annotated examples are required. This annotation task is performed by human oracles, which ends up in inaccuracies and errors in the annotations (aka ground truth) since the task is inherently very cumbersome and sometimes ambiguous. As an alternative we have pioneered the use of virtual worlds for collecting such annotations automatically and with high precision. However, since the models learned with virtual data must operate in the real world, we still need to perform domain adaptation (DA). In this chapter we revisit the DA of a deformable part-based model (DPM) as an exemplifying case of virtual- to-real-world DA. As a use case, we address the challenge of vehicle detection for driver assistance, using different publicly available virtual-world data. While doing so, we investigate questions such as: how does the domain gap behave due to virtual-vs-real data with respect to dominant object appearance per domain, as well as the role of photo-realism in the virtual world. | ||||
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Publisher | Springer | Place of Publication | Editor | Gabriela Csurka | |
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Notes | ADAS; 600.085; 601.223; 600.076; 600.118 | Approved | no | ||
Call Number | ADAS @ adas @ LXG2017 | Serial | 2872 | ||
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Author | German Ros; Laura Sellart; Gabriel Villalonga; Elias Maidanik; Francisco Molero; Marc Garcia; Adriana Cedeño; Francisco Perez; Didier Ramirez; Eduardo Escobar; Jose Luis Gomez; David Vazquez; Antonio Lopez | ||||
Title | Semantic Segmentation of Urban Scenes via Domain Adaptation of SYNTHIA | Type | Book Chapter | ||
Year | 2017 | Publication | Domain Adaptation in Computer Vision Applications | Abbreviated Journal | |
Volume | 12 | Issue | Pages | 227-241 | |
Keywords | SYNTHIA; Virtual worlds; Autonomous Driving | ||||
Abstract | Vision-based semantic segmentation in urban scenarios is a key functionality for autonomous driving. Recent revolutionary results of deep convolutional neural networks (DCNNs) foreshadow the advent of reliable classifiers to perform such visual tasks. However, DCNNs require learning of many parameters from raw images; thus, having a sufficient amount of diverse images with class annotations is needed. These annotations are obtained via cumbersome, human labour which is particularly challenging for semantic segmentation since pixel-level annotations are required. In this chapter, we propose to use a combination of a virtual world to automatically generate realistic synthetic images with pixel-level annotations, and domain adaptation to transfer the models learnt to correctly operate in real scenarios. We address the question of how useful synthetic data can be for semantic segmentation – in particular, when using a DCNN paradigm. In order to answer this question we have generated a synthetic collection of diverse urban images, named SYNTHIA, with automatically generated class annotations and object identifiers. We use SYNTHIA in combination with publicly available real-world urban images with manually provided annotations. Then, we conduct experiments with DCNNs that show that combining SYNTHIA with simple domain adaptation techniques in the training stage significantly improves performance on semantic segmentation. | ||||
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Publisher | Springer | Place of Publication | Editor | Gabriela Csurka | |
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Notes | ADAS; 600.085; 600.082; 600.076; 600.118 | Approved | no | ||
Call Number | ADAS @ adas @ RSV2017 | Serial | 2882 | ||
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Author | Ernest Valveny; Philippe Dosch | ||||
Title | Performance Evaluation of Symbol Recognition | Type | Book Chapter | ||
Year | 2004 | Publication | Document Analysis Systems | Abbreviated Journal | LNCS |
Volume | 3163 | Issue | Pages | 354–365 | |
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Address | Springer-Verlag | ||||
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Publisher | Place of Publication | Editor | S. Marinai, A. Dengel (Eds.), | ||
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ISSN | ISBN | 3-540-23060-2 | Medium | ||
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Notes | DAG | Approved | no | ||
Call Number | DAG @ dag @ VaD2004a | Serial | 502 | ||
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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 | Abbreviated Journal | |
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Address | Springer London | ||||
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Notes | DAG | Approved | no | ||
Call Number | DAG @ dag @ Lla2007 | Serial | 780 | ||
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Author | Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez | ||||
Title | Trajectory-Based Abnormality Categorization for Learning Route Patterns in Surveillance | Type | Book Chapter | ||
Year | 2012 | Publication | Detection and Identification of Rare Audiovisual Cues, Studies in Computational Intelligence | Abbreviated Journal | |
Volume | 384 | Issue | 3 | Pages | 87-95 |
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Abstract | The recognition of abnormal behaviors in video sequences has raised as a hot topic in video understanding research. Particularly, an important challenge resides on automatically detecting abnormality. However, there is no convention about the types of anomalies that training data should derive. In surveillance, these are typically detected when new observations differ substantially from observed, previously learned behavior models, which represent normality. This paper focuses on properly defining anomalies within trajectory analysis: we propose a hierarchical representation conformed by Soft, Intermediate, and Hard Anomaly, which are identified from the extent and nature of deviation from learned models. Towards this end, a novel Gaussian Mixture Model representation of learned route patterns creates a probabilistic map of the image plane, which is applied to detect and classify anomalies in real-time. Our method overcomes limitations of similar existing approaches, and performs correctly even when the tracking is affected by different sources of noise. The reliability of our approach is demonstrated experimentally. | ||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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ISSN | 1860-949X | ISBN | 978-3-642-24033-1 | Medium | |
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Notes | ISE | Approved | no | ||
Call Number | Admin @ si @ BFR2012 | Serial | 2062 | ||
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Author | Marçal Rusiñol; Josep Llados | ||||
Title | Flowchart Recognition in Patent Information Retrieval | Type | Book Chapter | ||
Year | 2017 | Publication | Current Challenges in Patent Information Retrieval | Abbreviated Journal | |
Volume | 37 | Issue | Pages | 351-368 | |
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | M. Lupu; K. Mayer; N. Kando; A.J. Trippe | |
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Notes | DAG; 600.097; 600.121 | Approved | no | ||
Call Number | Admin @ si @ RuL2017 | Serial | 2896 | ||
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