Publicacions CVC -- Query Results

	Publicacions CVC Home \| Show All \| Simple Search \| Advanced Search \| Add Record \| Import	Login Quick Search: Field: contains: ...
	1036–1050 of 3413 records found matching your query (RSS \| history):

Search & Display Options

Select All Deselect All

[51–60] << 61 62 63 64 65 66 67 68 69 70 >> [71–80]

List View

Citations

Details

	Records
	Author	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	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	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	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	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	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	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	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	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	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	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	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	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	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	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 classication 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 classiers. In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for the combination of classiers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classiers, 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 classiers. Evolutionary computation is used for tuning the parameters of the classiers and looking for the best Minimal ECOC code conguration. 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