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David Geronimo; Angel Sappa; Antonio Lopez; Daniel Ponsa |
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Title |
Adaptive Image Sampling and Windows Classification for On-board Pedestrian Detection |
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2007 |
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Proceedings of the 5th International Conference on Computer Vision Systems |
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ICVS |
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Pedestrian Detection |
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On–board pedestrian detection is in the frontier of the state–of–the–art since it implies processing outdoor scenarios from a mobile platform and searching for aspect–changing objects in cluttered urban environments. Most promising approaches include the development of classifiers based on feature selection and machine learning. However, they use a large number of features which compromises real–time. Thus, methods for running the classifiers in only a few image windows must be provided. In this paper we contribute in both aspects, proposing a camera
pose estimation method for adaptive sparse image sampling, as well as a classifier for pedestrian detection based on Haar wavelets and edge orientation histograms as features and AdaBoost as learning machine. Both proposals are compared with relevant approaches in the literature, showing comparable results but reducing processing time by four for the sampling tasks and by ten for the classification one. |
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Bielefeld (Germany) |
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ADAS @ adas @ gsl2007a |
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786 |
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Bogdan Raducanu; Jordi Vitria |
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Online Learning for Human-Robot Interaction |
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2007 |
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IEEE Conference on Computer Vision and Pattern Recognition Workshop on |
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Minneapolis (USA) |
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OR; MV |
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BCNPCL @ bcnpcl @ RaV2007a |
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791 |
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Pau Baiget; Joan Soto; Xavier Roca; Jordi Gonzalez |
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Title |
Automatic Generation of Computer-Animated Sequences based on Human Behaviour Modelling |
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2007 |
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10th International Conference on Computer Graphics and Artificial Intelligence |
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Athens (Greece) |
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3IA |
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ISE @ ise @ BSR2007 |
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808 |
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Oriol Ramos Terrades; Salvatore Tabbone; Ernest Valveny |
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Optimal Linear Combination for Two-class Classifiers |
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2007 |
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Proceedings of the International Conference on Advances in Pattern Recognition |
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Kolkata (India) |
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DAG @ dag @ RTV2007a |
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894 |
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Sergio Escalera; Petia Radeva; Oriol Pujol |
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Title |
Complex Salient Regions for Computer Vision Problems |
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2007 |
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IEEE Conference on Computer Vision and Pattern Recognition Workshop on |
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Minneapolis (USA) |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ ERP2007 |
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908 |
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Jaume Amores; N. Sebe; Petia Radeva |
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Title |
Class-Specific Binaryy Correlograms for Object Recognition |
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2007 |
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British Machine Vision Conference |
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Warwick (UK) |
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BMVC’07 |
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ADAS @ adas @ ASR2007a |
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923 |
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Daniel Ponsa; Antonio Lopez |
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Title |
Cascade of Classifiers for Vehicle Detection |
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2007 |
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Advanced Concepts for Intelligent Vision Systems, LNCS 4678, volume 1, pp. 980–989 |
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vehicle detection |
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Delft (Netherlands) |
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ADAS @ adas @ PoL2007c |
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935 |
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Jose Manuel Alvarez; Antonio Lopez; Ramon Baldrich |
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Title |
Shadow Resistant Road Segmentation from a Mobile Monocular System |
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2007 |
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3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4477:9–16 |
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road detection |
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Gerona (Spain) |
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ADAS @ adas @ ALB2007 |
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943 |
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Author |
Debora Gil; Jaume Garcia; Mariano Vazquez; Ruth Aris; Guilleaume Houzeaux |
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Title |
Patient-Sensitive Anatomic and Functional 3D Model of the Left Ventricle Function |
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Conference Article |
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2008 |
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8th World Congress on Computational Mechanichs (WCCM8) |
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Left Ventricle, Electromechanical Models, Image Processing, Magnetic Resonance. |
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Early diagnosis and accurate treatment of Left Ventricle (LV) dysfunction significantly increases the patient survival. Impairment of LV contractility due to cardiovascular diseases is reflected in its motion patterns. Recent advances in medical imaging, such as Magnetic Resonance (MR), have encouraged research on 3D simulation and modelling of the LV dynamics. Most of the existing 3D models [1] consider just the gross anatomy of the LV and restore a truncated ellipse which deforms along the cardiac cycle. The contraction mechanics of any muscle strongly depends on the spatial orientation of its muscular fibers since the motion that the muscle undergoes mainly takes place along the fibers. It follows that such simplified models do not allow evaluation of the heart electro-mechanical function and coupling, which has recently risen as the key point for understanding the LV functionality [2]. In order to thoroughly understand the LV mechanics it is necessary to consider the complete anatomy of the LV given by the orientation of the myocardial fibres in 3D space as described by Torrent Guasp [3].
We propose developing a 3D patient-sensitive model of the LV integrating, for the first time, the ven- tricular band anatomy (fibers orientation), the LV gross anatomy and its functionality. Such model will represent the LV function as a natural consequence of its own ventricular band anatomy. This might be decisive in restoring a proper LV contraction in patients undergoing pace marker treatment.
The LV function is defined as soon as the propagation of the contractile electromechanical pulse has been modelled. In our experiments we have used the wave equation for the propagation of the electric pulse. The electromechanical wave moves on the myocardial surface and should have a conductivity tensor oriented along the muscular fibers. Thus, whatever mathematical model for electric pulse propa- gation [4] we consider, the complete anatomy of the LV should be extracted.
The LV gross anatomy is obtained by processing multi slice MR images recorded for each patient. Information about the myocardial fibers distribution can only be extracted by Diffusion Tensor Imag- ing (DTI), which can not provide in vivo information for each patient. As a first approach, we have
Figure 1: Scheme for the Left Ventricle Patient-Sensitive Model.
computed an average model of fibers from several DTI studies of canine hearts. This rough anatomy is the input for our electro-mechanical propagation model simulating LV dynamics. The average fiber orientation is updated until the simulated LV motion agrees with the experimental evidence provided by the LV motion observed in tagged MR (TMR) sequences. Experimental LV motion is recovered by applying image processing, differential geometry and interpolation techniques to 2D TMR slices [5]. The pipeline in figure 1 outlines the interaction between simulations and experimental data leading to our patient-tailored model. |
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Venice; Italy |
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9788496736559 |
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IAM; |
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IAM @ iam @ GGV2008b |
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993 |
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Sergio Escalera; Oriol Pujol; J. Mauri; Petia Radeva |
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Title |
IVUS Tissue Characterization with Sub-class Error-correcting Output Codes |
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2008 |
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Computer Vision and Pattern Recognition Workshops, 2008. CVPR Workshops 2008. IEEE Computer Society Conference on, pp. 1–8, 23–28 juny 2008. |
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Intravascular ultrasound (IVUS) represents a powerful imaging technique to explore coronary vessels and to study their morphology and histologic properties. In this paper, we characterize different tissues based on Radio Frequency, texture-based, slope-based, and combined features. To deal with the classification of multiple tissues, we require the use of robust multi-class learning techniques. In this context, we propose a strategy to model multi-class classification tasks using sub-classes information in the ECOC framework. The new strategy splits the classes into different subsets according to the applied base classifier. Complex IVUS data sets containing overlapping data are learnt by splitting the original set of classes into sub-classes, and embedding the binary problems in a problem-dependent ECOC design. The method automatically characterizes different tissues, showing performance improvements over the state-of-the-art ECOC techniques for different base classifiers and feature sets. |
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BCNPCL @ bcnpcl @ EPM2008 |
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1041 |
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Miquel Ferrer; Ernest Valveny; F. Serratosa; K. Riesen; Horst Bunke |
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An Approximate Algorith for Median Graph Computation using Graph Embedding |
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2008 |
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19th International Conference on Pattern Recognition. |
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Tampa, USA |
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Dimosthenis Karatzas; Marçal Rusiñol; Coen Antens; Miquel Ferrer |
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Segmentation Robust to the Vignette Effect for Machine Vision Systems |
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2008 |
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19th International Conference on Pattern Recognition |
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The vignette effect (radial fall-off) is commonly encountered in images obtained through certain image acquisition setups and can seriously hinder automatic analysis processes. In this paper we present a fast and efficient method for dealing with vignetting in the context of object segmentation in an existing industrial inspection setup. The vignette effect is modelled here as a circular, non-linear gradient. The method estimates the gradient parameters and employs them to perform segmentation. Segmentation results on a variety of images indicate that the presented method is able to successfully tackle the vignette effect. |
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Tampa, USA |
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Partha Pratim Roy; Umapada Pal; Josep Llados; F. Kimura |
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Convex Hull based Approach for Multi-oriented Character Recognition form Graphical Documents |
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2008 |
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19th International Conference on Pattern Recognition |
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Jose Antonio Rodriguez; Florent Perronnin; Gemma Sanchez; Josep Llados |
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Unsupervised writer style adaptation for handwritten word spotting |
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2008 |
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Pattern Recognition. 19th International Conference on, IBM Best Student Paper Award. |
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DAG @ dag @ RPS2008 |
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1077 |
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Francisco Javier Orozco; Jordi Gonzalez |
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Confidence Assessment on Eyelid and Eyebrow Expression Recognition |
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2008 |
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2008 8th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2008) |
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Amsterdam (Holanda) |
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ISBN |
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Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
ISE |
Approved |
no |
|
| |
Call Number |
ISE @ ise @ OrG2008 |
Serial |
1111 |
|
| Permanent link to this record |
