Home [51–60] << 61 62 63 64 65 66 67 68 69 70 >> [71–80]
List View
 | 
Citations
 | 
Details
   web
Records
Author (down) Miguel Reyes; Jordi Vitria; Petia Radeva; Sergio Escalera
Title Real-time Activity Monitoring of Inpatients Type Conference Article
Year 2010 Publication Medical Image Computing in Catalunya: Graduate Student Workshop Abbreviated Journal
Volume Issue Pages 35–36
Keywords
Abstract In this paper, we present the development of an application capable of monitoring a set of patient vital signs in real time. The application has been designed to support the medical staff of a hospital. Preliminary results show the suitability
of the system to prevent the injury produced by the agitation of the patients.
Address Girona
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference MICCAT
Notes OR;MILAB;HUPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ RVR2010 Serial 1477
Permanent link to this record
 
 
Author (down) Miguel Reyes; Gabriel Dominguez; Sergio Escalera
Title Feature Weighting in Dynamic Time Warping for Gesture Recognition in Depth Data Type Conference Article
Year 2011 Publication 1st IEEE Workshop on Consumer Depth Cameras for Computer Vision Abbreviated Journal
Volume Issue Pages 1182-1188
Keywords
Abstract We present a gesture recognition approach for depth video data based on a novel Feature Weighting approach within the Dynamic Time Warping framework. Depth features from human joints are compared through video sequences using Dynamic Time Warping, and weights are assigned to features based on inter-intra class gesture variability. Feature Weighting in Dynamic Time Warping is then applied for recognizing begin-end of gestures in data sequences. The obtained results recognizing several gestures in depth data show high performance compared with classical Dynamic Time Warping approach.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-4673-0062-9 Medium
Area Expedition Conference CDC4CV
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ RDE2011 Serial 1893
Permanent link to this record
 
 
Author (down) Miguel Reyes; Albert Clapes; Luis Felipe Mejia; Jose Ramirez; Juan R Revilla; Sergio Escalera
Title Posture Analysis and Range of Movement Estimation using Depth Maps Type Conference Article
Year 2012 Publication 21st International Conference on Pattern Recognition International Workshop on Depth Image Analysis Abbreviated Journal
Volume 7854 Issue Pages 97-105
Keywords
Abstract World Health Organization estimates that 80% of the world population is affected of back pain during his life. Current practices to analyze back problems are expensive, subjective, and invasive. In this work, we propose a novel tool for posture and range of movement estimation based on the analysis of 3D information from depth maps. Given a set of keypoints defined by the user, RGB and depth data are aligned, depth surface is reconstructed, keypoints are matching using a novel point-to-point fitting procedure, and accurate measurements about posture, spinal curvature, and range of movement are computed. The system shows high precision and reliable measurements, being useful for posture reeducation purposes to prevent musculoskeletal disorders, such as back pain, as well as tracking the posture evolution of patients in rehabilitation treatments.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-40302-6 Medium
Area Expedition Conference WDIA
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ RCM2012 Serial 2121
Permanent link to this record
 
 
Author (down) Miguel Reyes; Albert Clapes; Jose Ramirez; Juan R Revilla; Sergio Escalera
Title Automatic Digital Biometry Analysis based on Depth Maps Type Journal Article
Year 2013 Publication Computers in Industry Abbreviated Journal COMPUTIND
Volume 64 Issue 9 Pages 1316-1325
Keywords Multi-modal data fusion; Depth maps; Posture analysis; Anthropometric data; Musculo-skeletal disorders; Gesture analysis
Abstract World Health Organization estimates that 80% of the world population is affected by back-related disorders during his life. Current practices to analyze musculo-skeletal disorders (MSDs) are expensive, subjective, and invasive. In this work, we propose a tool for static body posture analysis and dynamic range of movement estimation of the skeleton joints based on 3D anthropometric information from multi-modal data. Given a set of keypoints, RGB and depth data are aligned, depth surface is reconstructed, keypoints are matched, and accurate measurements about posture and spinal curvature are computed. Given a set of joints, range of movement measurements is also obtained. Moreover, gesture recognition based on joint movements is performed to look for the correctness in the development of physical exercises. The system shows high precision and reliable measurements, being useful for posture reeducation purposes to prevent MSDs, as well as tracking the posture evolution of patients in rehabilitation treatments.
Address
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ RCR2013 Serial 2252
Permanent link to this record
 
 
Author (down) Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias; A. Moreira
Title Incremental Scenario Representations for Autonomous Driving using Geometric Polygonal Primitives Type Journal Article
Year 2016 Publication Robotics and Autonomous Systems Abbreviated Journal RAS
Volume 83 Issue Pages 312-325
Keywords Incremental scene reconstruction; Point clouds; Autonomous vehicles; Polygonal primitives
Abstract When an autonomous vehicle is traveling through some scenario it receives a continuous stream of sensor data. This sensor data arrives in an asynchronous fashion and often contains overlapping or redundant information. Thus, it is not trivial how a representation of the environment observed by the vehicle can be created and updated over time. This paper presents a novel methodology to compute an incremental 3D representation of a scenario from 3D range measurements. We propose to use macro scale polygonal primitives to model the scenario. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Furthermore, we propose mechanisms designed to update the geometric polygonal primitives over time whenever fresh sensor data is collected. Results show that the approach is capable of producing accurate descriptions of the scene, and that it is computationally very efficient when compared to other reconstruction techniques.
Address
Corporate Author Thesis
Publisher Elsevier B.V. Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ADAS; 600.086, 600.076 Approved no
Call Number Admin @ si @OSS2016a Serial 2806
Permanent link to this record
 
 
Author (down) Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias; A. Moreira
Title Incremental texture mapping for autonomous driving Type Journal Article
Year 2016 Publication Robotics and Autonomous Systems Abbreviated Journal RAS
Volume 84 Issue Pages 113-128
Keywords Scene reconstruction; Autonomous driving; Texture mapping
Abstract Autonomous vehicles have a large number of on-board sensors, not only for providing coverage all around the vehicle, but also to ensure multi-modality in the observation of the scene. Because of this, it is not trivial to come up with a single, unique representation that feeds from the data given by all these sensors. We propose an algorithm which is capable of mapping texture collected from vision based sensors onto a geometric description of the scenario constructed from data provided by 3D sensors. The algorithm uses a constrained Delaunay triangulation to produce a mesh which is updated using a specially devised sequence of operations. These enforce a partial configuration of the mesh that avoids bad quality textures and ensures that there are no gaps in the texture. Results show that this algorithm is capable of producing fine quality textures.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ADAS; 600.086 Approved no
Call Number Admin @ si @ OSS2016b Serial 2912
Permanent link to this record
 
 
Author (down) Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias
Title Scene Representations for Autonomous Driving: an approach based on polygonal primitives Type Conference Article
Year 2015 Publication 2nd Iberian Robotics Conference ROBOT2015 Abbreviated Journal
Volume 417 Issue Pages 503-515
Keywords Scene reconstruction; Point cloud; Autonomous vehicles
Abstract In this paper, we present a novel methodology to compute a 3D scene
representation. The algorithm uses macro scale polygonal primitives to model the scene. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Results show that the approach is capable of producing accurate descriptions of the scene. In addition, the algorithm is very efficient when compared to other techniques.
Address Lisboa; Portugal; November 2015
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference ROBOT
Notes ADAS; 600.076; 600.086 Approved no
Call Number Admin @ si @ OSS2015a Serial 2662
Permanent link to this record
 
 
Author (down) Miguel Oliveira; Victor Santos; Angel Sappa
Title Multimodal Inverse Perspective Mapping Type Journal Article
Year 2015 Publication Information Fusion Abbreviated Journal IF
Volume 24 Issue Pages 108–121
Keywords Inverse perspective mapping; Multimodal sensor fusion; Intelligent vehicles
Abstract Over the past years, inverse perspective mapping has been successfully applied to several problems in the field of Intelligent Transportation Systems. In brief, the method consists of mapping images to a new coordinate system where perspective effects are removed. The removal of perspective associated effects facilitates road and obstacle detection and also assists in free space estimation. There is, however, a significant limitation in the inverse perspective mapping: the presence of obstacles on the road disrupts the effectiveness of the mapping. The current paper proposes a robust solution based on the use of multimodal sensor fusion. Data from a laser range finder is fused with images from the cameras, so that the mapping is not computed in the regions where obstacles are present. As shown in the results, this considerably improves the effectiveness of the algorithm and reduces computation time when compared with the classical inverse perspective mapping. Furthermore, the proposed approach is also able to cope with several cameras with different lenses or image resolutions, as well as dynamic viewpoints.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ADAS; 600.055; 600.076 Approved no
Call Number Admin @ si @ OSS2015c Serial 2532
Permanent link to this record
 
 
Author (down) Miguel Oliveira; V.Santos; Angel Sappa
Title Short term path planning using a multiple hypothesis evaluation approach for an autonomous driving competition Type Conference Article
Year 2012 Publication IEEE 4th Workshop on Planning, Perception and Navigation for Intelligent Vehicles Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Algarve; Portugal
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference PPNIV
Notes ADAS Approved no
Call Number Admin @ si @ OSS2012c Serial 2159
Permanent link to this record
 
 
Author (down) Miguel Oliveira; L. Seabra Lopes; G. Hyun Lim; S. Hamidreza Kasaei; Angel Sappa; A. Tom
Title Concurrent Learning of Visual Codebooks and Object Categories in Openended Domains Type Conference Article
Year 2015 Publication International Conference on Intelligent Robots and Systems Abbreviated Journal
Volume Issue Pages 2488 - 2495
Keywords Visual Learning; Computer Vision; Autonomous Agents
Abstract In open-ended domains, robots must continuously learn new object categories. When the training sets are created offline, it is not possible to ensure their representativeness with respect to the object categories and features the system will find when operating online. In the Bag of Words model, visual codebooks are constructed from training sets created offline. This might lead to non-discriminative visual words and, as a consequence, to poor recognition performance. This paper proposes a visual object recognition system which concurrently learns in an incremental and online fashion both the visual object category representations as well as the codebook words used to encode them. The codebook is defined using Gaussian Mixture Models which are updated using new object views. The approach contains similarities with the human visual object recognition system: evidence suggests that the development of recognition capabilities occurs on multiple levels and is sustained over large periods of time. Results show that the proposed system with concurrent learning of object categories and codebooks is capable of learning more categories, requiring less examples, and with similar accuracies, when compared to the classical Bag of Words approach using offline constructed codebooks.
Address Hamburg; Germany; October 2015
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference IROS
Notes ADAS; 600.076 Approved no
Call Number Admin @ si @ OSL2015 Serial 2664
Permanent link to this record
 
 
Author (down) Miguel Oliveira; Angel Sappa; Victor Santos
Title A probabilistic approach for color correction in image mosaicking applications Type Journal Article
Year 2015 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 14 Issue 2 Pages 508 - 523
Keywords Color correction; image mosaicking; color transfer; color palette mapping functions
Abstract Image mosaicking applications require both geometrical and photometrical registrations between the images that compose the mosaic. This paper proposes a probabilistic color correction algorithm for correcting the photometrical disparities. First, the image to be color corrected is segmented into several regions using mean shift. Then, connected regions are extracted using a region fusion algorithm. Local joint image histograms of each region are modeled as collections of truncated Gaussians using a maximum likelihood estimation procedure. Then, local color palette mapping functions are computed using these sets of Gaussians. The color correction is performed by applying those functions to all the regions of the image. An extensive comparison with ten other state of the art color correction algorithms is presented, using two different image pair data sets. Results show that the proposed approach obtains the best average scores in both data sets and evaluation metrics and is also the most robust to failures.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1057-7149 ISBN Medium
Area Expedition Conference
Notes ADAS; 600.076 Approved no
Call Number Admin @ si @ OSS2015b Serial 2554
Permanent link to this record
 
 
Author (down) Miguel Oliveira; Angel Sappa; V.Santos
Title Unsupervised Local Color Correction for Coarsely Registered Images Type Conference Article
Year 2011 Publication IEEE conference on Computer Vision and Pattern Recognition Abbreviated Journal
Volume Issue Pages 201-208
Keywords
Abstract The current paper proposes a new parametric local color correction technique. Initially, several color transfer functions are computed from the output of the mean shift color segmentation algorithm. Secondly, color influence maps are calculated. Finally, the contribution of every color transfer function is merged using the weights from the color influence maps. The proposed approach is compared with both global and local color correction approaches. Results show that our method outperforms the technique ranked first in a recent performance evaluation on this topic. Moreover, the proposed approach is computed in about one tenth of the time.
Address Colorado Springs
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1063-6919 ISBN 978-1-4577-0394-2 Medium
Area Expedition Conference CVPR
Notes ADAS Approved no
Call Number Admin @ si @ OSS2011; ADAS @ adas @ Serial 1766
Permanent link to this record
 
 
Author (down) Miguel Oliveira; Angel Sappa; V. Santos
Title Color Correction for Onboard Multi-camera Systems using 3D Gaussian Mixture Models Type Conference Article
Year 2012 Publication IEEE Intelligent Vehicles Symposium Abbreviated Journal
Volume Issue Pages 299-303
Keywords
Abstract The current paper proposes a novel color correction approach for onboard multi-camera systems. It works by segmenting the given images into several regions. A probabilistic segmentation framework, using 3D Gaussian Mixture Models, is proposed. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. An image data set of road scenarios is used to establish a performance comparison of the proposed method with other seven well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches.
Address Alcalá de Henares
Corporate Author Thesis
Publisher IEEE Xplore Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1931-0587 ISBN 978-1-4673-2119-8 Medium
Area Expedition Conference IV
Notes ADAS Approved no
Call Number Admin @ si @ OSS2012b Serial 2021
Permanent link to this record
 
 
Author (down) Miguel Oliveira; Angel Sappa; V. Santos
Title Color Correction using 3D Gaussian Mixture Models Type Conference Article
Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal
Volume 7324 Issue I Pages 97-106
Keywords
Abstract The current paper proposes a novel color correction approach based on a probabilistic segmentation framework by using 3D Gaussian Mixture Models. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. The proposed approach is evaluated using both a recently published metric and two large data sets composed of seventy images. The evaluation is performed by comparing our algorithm with eight well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 10.1007/978-3-642-31295-3_12 Medium
Area Expedition Conference ICIAR
Notes ADAS Approved no
Call Number Admin @ si @ OSS2012a Serial 2015
Permanent link to this record
 
 
Author (down) Miguel Angel Bautista; Xavier Baro; Oriol Pujol; Petia Radeva; Jordi Vitria; Sergio Escalera
Title Compact Evolutive Design of Error-Correcting Output Codes Type Conference Article
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 Abbreviated Journal
Volume Issue Pages 119-128
Keywords Ensemble of Dichotomizers; Error-Correcting Output Codes; Evolutionary optimization
Abstract The classi cation of large number of object categories is a challenging trend in the Machine Learning eld. In literature, this is often addressed using an ensemble of classi ers. In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for the combination of classi ers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classi ers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a minimal design of ECOC in terms of the number of classi ers. Evolutionary computation is used for tuning the parameters of the classi ers and looking for the best Minimal ECOC code con guration. The results over several public UCI data sets and a challenging multi-class Computer Vision problem show that the proposed methodology obtains comparable and even better results than state-of-the-art ECOC methodologies with far less number of dichotomizers.
Address Barcelona (Spain)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference SUEMA
Notes OR;MILAB;HUPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ BBP2010 Serial 1363
Permanent link to this record