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Author |
Javier Marin |
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Title |
Virtual learning for real testing |
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Report |
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2009 |
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CVC Technical Report |
Abbreviated Journal |
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150 |
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Computer Vision Center |
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Master's thesis |
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bell |
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ADAS |
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no |
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Admin @ si @ Mar2009c |
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2403 |
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Author |
Ivet Rafegas |
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Title |
Exploring Low-Level Vision Models. Case Study: Saliency Prediction |
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2013 |
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CVC Technical Report |
Abbreviated Journal |
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175 |
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CIC |
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no |
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Admin @ si @ Raf2013 |
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2409 |
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Author |
Francesco Brughi |
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Title |
Artistic Heritage Motive Retrieval: an Explorative Study |
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2013 |
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CVC Technical Report |
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176 |
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IAM |
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Admin @ si @ Bru2013 |
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2410 |
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Author |
German Ros |
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Title |
Visual SLAM for Driverless Cars: An Initial Survey |
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2012 |
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CVC Technical Report |
Abbreviated Journal |
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170 |
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ADAS |
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no |
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Admin @ si @ Ros2012c |
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2414 |
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Author |
Xu Hu |
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Title |
Real-Time Part Based Models for Object Detection |
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2012 |
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CVC Technical Report |
Abbreviated Journal |
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171 |
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ADAS;ISE |
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no |
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Admin @ si @ Hu2012 |
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2415 |
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Author |
Nuria Cirera |
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Title |
Recognition of Handwritten Historical Documents |
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Report |
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Year |
2012 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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174 |
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DAG |
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no |
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Admin @ si @ Cir2012 |
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2416 |
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Author |
Antonio Esteban Lansaque |
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Title |
3D reconstruction and recognition using structured ligth |
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Report |
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Year |
2014 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
179 |
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Abstract |
This work covers the problem of 3D reconstruction, recognition and 6DOF pose estimation. The goal of this project is to reconstruct a 3D scene and to align an object model of the industrial pieces onto the reconstructed scene. The reconstruction algorithm is based on stereo techniques and the recognition algorithm is based on SHOT descriptors computed on a set of uniform keypoints. Correspondences are used to estimate a first 6DOF transformation that maps the model onto the scene and then ICP algorithm is used to refine the transformation. In order to check the effectiveness of the proposed algorithm, several experiments were performed. These experiments were conducted on a lab environment in order to get results under the same conditions in all of them. Although obtained results are not real time results, the proposed algorithm ends up with high rates of object recognition. |
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UAB; September 2014 |
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Master's thesis |
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Notes |
IAM; 600.075 |
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no |
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Call Number |
Admin @ si @ Est2014 |
Serial |
2578 |
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Author |
Ricard Balague |
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Title |
Exploring the combination of color cues for intrinsic image decomposition |
Type |
Report |
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Year |
2014 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
178 |
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Intrinsic image decomposition is a challenging problem that consists in separating an image into its physical characteristics: reflectance and shading. This problem can be solved in different ways, but most methods have combined information from several visual cues. In this work we describe an extension of an existing method proposed by Serra et al. which considers two color descriptors and combines them by means of a Markov Random Field. We analyze in depth the weak points of the method and we explore more possibilities to use in both descriptors. The proposed extension depends on the combination of the cues considered to overcome some of the limitations of the original method. Our approach is tested on the MIT dataset and Beigpour et al. dataset, which contain images of real objects acquired under controlled conditions and synthetic images respectively, with their corresponding ground truth. |
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UAB; September 2014 |
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Master's thesis |
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CIC; 600.074 |
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no |
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Call Number |
Admin @ si @ Bal2014 |
Serial |
2579 |
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Permanent link to this record |
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Author |
Sebastian Ramos |
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Title |
Vision-based Detection of Road Hazards for Autonomous Driving |
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Report |
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Year |
2014 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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UAB; September 2014 |
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Master's thesis |
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ADAS; 600.076 |
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no |
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Call Number |
Admin @ si @ Ram2014 |
Serial |
2580 |
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Permanent link to this record |
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Author |
Albert Andaluz |
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Title |
LV Contour Segmentation in TMR images using Semantic Description of Tissue and Prior Knowledge Correction |
Type |
Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
142 |
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Keywords |
Active Contour Models; Snakes; Active Shape Models; Deformable Templates; Left Ventricle Segmentation; Generalized Orthogonal Procrustes Analysis; Harmonic Phase Flow; Principal Component Analysis; Tagged Magnetic Resonance |
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Abstract |
The Diagnosis of Left Ventricle (LV) pathologies is related to regional wall motion analysis. Health indicator scores such as the rotation and the torsion are useful for the diagnose of the Left Ventricle (LV) function. However, this requires proper identification of LV segments. On one hand, manual segmentation is robust, but it is slow and requires medical expertise. On the other hand, the tag pattern in Tagged Magnetic Resonance (TMR) sequences is a problem for the automatic segmentation of the LV boundaries. Consequently, we propose a method based in the classical formulation of parametric Snakes, combined with Active Shape models. Our semantic definition of the LV is tagged tissue that experiences motion in the systolic cycle. This defines two energy potentials for the Snake convergence. Additionally, the mean shape corrects excessive deviation from the anatomical shape. We have validated our approach in 15 healthy volunteers and two short axis cuts. In this way, we have compared the automatic segmentations to manual shapes outlined by medical experts. Also, we have explored the accuracy of clinical scores computed using automatic contours. The results show minor divergence in the approximation and the manual segmentations as well as robust computation of clinical scores in all cases. From this we conclude that the proposed method is a promising support tool for clinical analysis. |
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Master's thesis |
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Bellaterra 08193, Barcelona, Spain |
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IAM; |
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no |
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IAM @ iam @ And2009 |
Serial |
1667 |
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Permanent link to this record |
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Author |
Carles Sanchez |
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Title |
Tracheal ring detection in bronchoscopy |
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Report |
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Year |
2011 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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168 |
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Bronchoscopy, tracheal ring, segmentation |
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Abstract |
Endoscopy is the process in which a camera is introduced inside a human.
Given that endoscopy provides realistic images (in contrast to other modalities) and allows non-invase minimal intervention procedures (which can aid in diagnosis and surgical interventions), its use has spreaded during last decades.
In this project we will focus on bronchoscopic procedures, during which the camera is introduced through the trachea in order to have a diagnostic of the patient. The diagnostic interventions are focused on: degree of stenosis (reduction in tracheal area), prosthesis or early diagnosis of tumors. In the first case, assessment of the luminal area and the calculation of the diameters of the tracheal rings are required. A main limitation is that all the process is done by hand,
which means that the doctor takes all the measurements and decisions just by looking at the screen. As far as we know there is no computational framework for helping the doctors in the diagnosis.
This project will consist of analysing bronchoscopic videos in order to extract useful information for the diagnostic of the degree of stenosis. In particular we will focus on segmentation of the tracheal rings. As a result of this project several strategies (for detecting tracheal rings) had been implemented in order to compare their performance. |
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Master's thesis |
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Debora Gil, F.Javier Sanchez |
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english |
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english |
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IAM;MV |
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no |
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Call Number |
IAM @ iam @ San2011 |
Serial |
1841 |
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Permanent link to this record |
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Author |
Jaume Garcia |
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Title |
Generalized Active Shape Models Applied to Cardiac Function Analysis |
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Report |
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2004 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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78 |
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Keywords |
Cardiac Analysis; Deformable Models; Active Contour Models; Active Shape Models; Tagged MRI; HARP; Contrast Echocardiography. |
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Abstract |
Medical imaging is very useful in the assessment and treatment of many diseases. To deal with the great amount of data provided by imaging scanners and extract quantitative information that physicians can interpret, many analysis algorithms have been developed. Any process of analysis always consists of a first step of segmenting some particular structure. In medical imaging, structures are not always well defined and suffer from noise artifacts thus, ordinary segmentation methods are not well suited. The ones that seem to give better results are those based on deformable models. Nevertheless, despite their capability of mixing image features together with smoothness constraints that may compensate for image irregularities, these are naturally local methods, i. e., each node of the active contour evolve taking into account information about its neighbors and some other weak constraints about flexibility and smoothness, but not about the global shape that they should find. Due to the fact that structures to be segmented are the same for all cases but with some inter and intra-patient variation, the incorporation of a priori knowledge about shape in the segmentation method will provide robustness to it. Active Shape Models is an algorithm based on the creation of a shape model called Point Distribution Model. It performs a segmentation using only shapes similar than those previously learned from a training set that capture most of the variation presented by the structure. This algorithm works by updating shape nodes along a normal segment which often can be too restrictive. For this reason we propose a generalization of this algorithm that we call Generalized Active Shape Models and fully integrates the a priori knowledge given by the Point Distribution Model with deformable models or any other appropriate segmentation method. Two different applications to cardiac imaging of this generalized method are developed and promising results are shown. |
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CVC (UAB) |
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Master's thesis |
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IAM; |
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no |
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IAM @ iam @ Gar2004 |
Serial |
1513 |
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Permanent link to this record |
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Author |
Onur Ferhat |
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Title |
Eye-Tracking with Webcam-Based Setups: Implementation of a Real-Time System and an Analysis of Factors Affecting Performance |
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Report |
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Year |
2012 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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172 |
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Computer vision, eye-tracking, gaussian process, feature selection, optical flow |
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In the recent years commercial eye-tracking hardware has become more common, with the introduction of new models from several brands that have better performance and easier setup procedures. A cause and at the same time a result of this phenomenon is the popularity of eye-tracking research directed at marketing, accessibility and usability, among others.
One problem with these hardware components is scalability, because both the price and the necessary expertise to operate them makes it practically impossible in the large scale. In this work, we analyze the feasibility of a software eye-tracking system based on a single, ordinary webcam. Our aim is to discover the limits of such a system and to see whether it provides acceptable performances.
The significance of this setup is that it is the most common setup found in consumer environments, off-the-shelf electronic devices such as laptops, mobile phones and tablet computers. As no special equipment such as infrared lights, mirrors or zoom lenses are used; setting up and calibrating the system is easier compared to other approaches using these components.
Our work is based on the open source application Opengazer, which provides a good starting point for our contributions. We propose several improvements in order to push the system's performance further and make it feasible as a robust, real-time device. Then we carry out an elaborate experiment involving 18 human subjects and 4 different system setups. Finally, we give an analysis of the results and discuss the effects of setup changes, subject differences and modifications in the software. |
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Bellaterra |
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Corporate Author |
Computer Vision Center |
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Master's thesis |
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Fernando Vilariño |
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MV |
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no |
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Admin @ si @ Fer2012; IAM @ iam @ Fer2012 |
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2165 |
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Permanent link to this record |
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Author |
Daniel Hernandez; Alejandro Chacon; Antonio Espinosa; David Vazquez; Juan Carlos Moure; Antonio Lopez |
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Title |
Stereo Matching using SGM on the GPU |
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2016 |
Publication |
Programming and Tuning Massively Parallel Systems |
Abbreviated Journal |
PUMPS |
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CUDA; Stereo; Autonomous Vehicle |
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Dense, robust and real-time computation of depth information from stereo-camera systems is a computationally demanding requirement for robotics, advanced driver assistance systems (ADAS) and autonomous vehicles. Semi-Global Matching (SGM) is a widely used algorithm that propagates consistency constraints along several paths across the image. This work presents a real-time system producing reliable disparity estimation results on the new embedded energy efficient GPU devices. Our design runs on a Tegra X1 at 42 frames per second (fps) for an image size of 640x480, 128 disparity levels, and using 4 path directions for the SGM method. |
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PUMPS |
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ADAS; 600.085; 600.087; 600.076 |
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no |
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ADAS @ adas @ HCE2016b |
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2776 |
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Permanent link to this record |
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Author |
David Vazquez; Antonio Lopez |
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Title |
Intrusion Classification in Intelligent Video Surveillance Systems |
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Report |
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Year |
2008 |
Publication |
Estudis d'Enginyeria Superior en Informática |
Abbreviated Journal |
UAB |
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Keywords |
Human detection; Car detection; Intrusion detection |
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Abstract |
An intelligent video surveillance system (IVS) is a camera-based installation able to process in real-time the images coming from the cameras. The aim is to automatically warn about different events of interest at the moment they happen. Daview system of Davantis is a com mercial example of IVS system. The problems addressed by any IVS system, and so Daview, are so challenging that none IVS system is perfect, thus, they need continuous improvement. Accordingly, this project aims to study different approaches in order to outperform current Daview performance, in particular, we bet for improving its classification core. We present an in deep study of the state of the art on IVS systems, as well as on how Daview works. Based on that knowledge, we propose four possibilities for improving Daview classification capabilities: improve existent classifiers; improve existing classifiers combination; create new classifiers and create new classifier-based architectures. Our main contribution has been the incorporation of state-of-the-art feature selection and machine learning techniques for the classification tasks, a viewpoint not fully addressed in current Daview system. After a comprehensive quantitative evaluation we will see how one of our proposals clearly outperforms the overall performance of current Daview system. In particular the classification core that we finally propose consists in an AdaBoost One-Against-All architecture that uses appearance and motion features that were already present in current Daview system |
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Bellaterra, Spain |
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ADAS @ adas @ VL2008a |
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1670 |
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