Publicacions CVC -- Query Results

	Publicacions CVC Home \| Show All \| Simple Search \| Advanced Search \| Add Record \| Import	Login Quick Search: Field: contains: ...
	2086–2100 of 3413 records found matching your query (RSS):

Search & Display Options

Select All Deselect All

[121–130] << 131 132 133 134 135 136 137 138 139 140 >> [141–150]

List View

Citations

Details

	Records
	Author	Ivan Huerta; Ariel Amato; Jordi Gonzalez; Juan J. Villanueva
	Title	Fusing Edge Cues to Handle Colour Problems in Image Segmentation			Type	Book Chapter
	Year	2008	Publication	Articulated Motion and Deformable Objects, 5th International Conference	Abbreviated Journal
	Volume	5098	Issue		Pages	279–288
	Keywords
	Abstract
	Address	Port d'Andratx (Mallorca)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	AMDO
	Notes	ISE			Approved	no
	Call Number	ISE @ ise @ HAG2008			Serial	973
Permanent link to this record



	Author	Bhaskar Chakraborty; Marco Pedersoli; Jordi Gonzalez
	Title	View-Invariant Human Action Detection using Component-Wise HMM of Body Parts			Type	Book Chapter
	Year	2008	Publication	Articulated Motion and Deformable Objects, 5th International Conference	Abbreviated Journal
	Volume	5098	Issue		Pages	208–217
	Keywords
	Abstract
	Address	Port d'Andratx (Mallorca)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	AMDO
	Notes	ISE			Approved	no
	Call Number	ISE @ ise @ CPG2008			Serial	975
Permanent link to this record



	Author	Wenjuan Gong; Andrew Bagdanov; Xavier Roca; Jordi Gonzalez
	Title	Automatic Key Pose Selection for 3D Human Action Recognition			Type	Conference Article
	Year	2010	Publication	6th International Conference on Articulated Motion and Deformable Objects	Abbreviated Journal
	Volume	6169	Issue		Pages	290–299
	Keywords
	Abstract	This article describes a novel approach to the modeling of human actions in 3D. The method we propose is based on a “bag of poses” model that represents human actions as histograms of key-pose occurrences over the course of a video sequence. Actions are first represented as 3D poses using a sequence of 36 direction cosines corresponding to the angles 12 joints form with the world coordinate frame in an articulated human body model. These pose representations are then projected to three-dimensional, action-specific principal eigenspaces which we refer to as aSpaces. We introduce a method for key-pose selection based on a local-motion energy optimization criterion and we show that this method is more stable and more resistant to noisy data than other key-poses selection criteria for action recognition.
	Address
	Corporate Author				Thesis
	Publisher	Springer Verlag	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	978-3-642-14060-0	Medium
	Area		Expedition		Conference	AMDO
	Notes	ISE			Approved	no
	Call Number	DAG @ dag @ GBR2010			Serial	1317
Permanent link to this record



	Author	Albert Clapes; Miguel Reyes; Sergio Escalera
	Title	User Identification and Object Recognition in Clutter Scenes Based on RGB-Depth Analysis			Type	Conference Article
	Year	2012	Publication	7th Conference on Articulated Motion and Deformable Objects	Abbreviated Journal
	Volume	7378	Issue		Pages	1-11
	Keywords
	Abstract	We propose an automatic system for user identification and object recognition based on multi-modal RGB-Depth data analysis. We model a RGBD environment learning a pixel-based background Gaussian distribution. Then, user and object candidate regions are detected and recognized online using robust statistical approaches over RGBD descriptions. Finally, the system saves the historic of user-object assignments, being specially useful for surveillance scenarios. The system has been evaluated on a novel data set containing different indoor/outdoor scenarios, objects, and users, showing accurate recognition and better performance than standard state-of-the-art approaches.
	Address	Mallorca
	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	978-3-642-31566-4	Medium
	Area		Expedition		Conference	AMDO
	Notes	HUPBA;MILAB			Approved	no
	Call Number	Admin @ si @ CRE2012			Serial	2010
Permanent link to this record



	Author	Wenjuan Gong; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca
	Title	A New Image Dataset on Human Interactions			Type	Conference Article
	Year	2012	Publication	7th Conference on Articulated Motion and Deformable Objects	Abbreviated Journal
	Volume	7378	Issue		Pages	204-209
	Keywords
	Abstract	This article describes a new collection of still image dataset which are dedicated to interactions between people. Human action recognition from still images have been a hot topic recently, but most of them are actions performed by a single person, like running, walking, riding bikes, phoning and so on and there is no interactions between people in one image. The dataset collected in this paper are concentrating on human interaction between two people aiming to explore this new topic in the research area of action recognition from still images.
	Address	Mallorca
	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	978-3-642-31566-4	Medium
	Area		Expedition		Conference	AMDO
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ GGT2012			Serial	2030
Permanent link to this record



	Author	Sergio Escalera
	Title	Human Behavior Analysis From Depth Maps			Type	Conference Article
	Year	2012	Publication	7th Conference on Articulated Motion and Deformable Objects	Abbreviated Journal
	Volume	7378	Issue		Pages	282-292
	Keywords
	Abstract	Pose Recovery (PR) and Human Behavior Analysis (HBA) have been a main focus of interest from the beginnings of Computer Vision and Machine Learning. PR and HBA were originally addressed by the analysis of still images and image sequences. More recent strategies consisted of Motion Capture technology (MOCAP), based on the synchronization of multiple cameras in controlled environments; and the analysis of depth maps from Time-of-Flight (ToF) technology, based on range image recording from distance sensor measurements. Recently, with the appearance of the multi-modal RGBD information provided by the low cost Kinect \textsfTM sensor (from RGB and Depth, respectively), classical methods for PR and HBA have been redefined, and new strategies have been proposed. In this paper, the recent contributions and future trends of multi-modal RGBD data analysis for PR and HBA are reviewed and discussed.
	Address	Mallorca
	Corporate Author				Thesis
	Publisher	Springer Heidelberg	Place of Publication		Editor	F.J. Perales; R.B. Fisher; T.B. Moeslund
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-31566-4	Medium
	Area		Expedition		Conference	AMDO
	Notes	MILAB; HuPBA			Approved	no
	Call Number	Admin @ si @ Esc2012			Serial	2040
Permanent link to this record



	Author	Oualid M. Benkarim; Petia Radeva; Laura Igual
	Title	Label Consistent Multiclass Discriminative Dictionary Learning for MRI Segmentation			Type	Conference Article
	Year	2014	Publication	8th Conference on Articulated Motion and Deformable Objects	Abbreviated Journal
	Volume	8563	Issue		Pages	138-147
	Keywords	MRI segmentation; sparse representation; discriminative dic- tionary learning; multiclass classication
	Abstract	The automatic segmentation of multiple subcortical structures in brain Magnetic Resonance Images (MRI) still remains a challenging task. In this paper, we address this problem using sparse representation and discriminative dictionary learning, which have shown promising results in compression, image denoising and recently in MRI segmentation. Particularly, we use multiclass dictionaries learned from a set of brain atlases to simultaneously segment multiple subcortical structures. We also impose dictionary atoms to be specialized in one given class using label consistent K-SVD, which can alleviate the bias produced by unbalanced libraries, present when dealing with small structures. The proposed method is compared with other state of the art approaches for the segmentation of the Basal Ganglia of 35 subjects of a public dataset. The promising results of the segmentation method show the eciency of the multiclass discriminative dictionary learning algorithms in MRI segmentation problems.
	Address	Palma de Mallorca; July 2014
	Corporate Author				Thesis
	Publisher	Springer International Publishing	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	978-3-319-08848-8	Medium
	Area		Expedition		Conference	AMDO
	Notes	MILAB; OR			Approved	no
	Call Number	Admin @ si @ BRI2014			Serial	2494
Permanent link to this record



	Author	Marc Bolaños; Maite Garolera; Petia Radeva
	Title	Video Segmentation of Life-Logging Videos			Type	Conference Article
	Year	2014	Publication	8th Conference on Articulated Motion and Deformable Objects	Abbreviated Journal
	Volume	8563	Issue		Pages	1-9
	Keywords
	Abstract
	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	AMDO
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @ BGR2014			Serial	2558
Permanent link to this record



	Author	Pejman Rasti; Tonis Uiboupin; Sergio Escalera; Gholamreza Anbarjafari
	Title	Convolutional Neural Network Super Resolution for Face Recognition in Surveillance Monitoring			Type	Conference Article
	Year	2016	Publication	9th Conference on Articulated Motion and Deformable Objects	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Palma de Mallorca; Spain; July 2016
	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	AMDO
	Notes	HuPBA;MILAB			Approved	no
	Call Number	Admin @ si @ RUE2016			Serial	2846
Permanent link to this record



	Author	Dennis H. Lundtoft; Kamal Nasrollahi; Thomas B. Moeslund; Sergio Escalera
	Title	Spatiotemporal Facial Super-Pixels for Pain Detection			Type	Conference Article
	Year	2016	Publication	9th Conference on Articulated Motion and Deformable Objects	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	Facial images; Super-pixels; Spatiotemporal filters; Pain detection
	Abstract	Best student paper award. Pain detection using facial images is of critical importance in many Health applications. Since pain is a spatiotemporal process, recent works on this topic employ facial spatiotemporal features to detect pain. These systems extract such features from the entire area of the face. In this paper, we show that by employing super-pixels we can divide the face into three regions, in a way that only one of these regions (about one third of the face) contributes to the pain estimation and the other two regions can be discarded. The experimental results on the UNBCMcMaster database show that the proposed system using this single region outperforms state-of-the-art systems in detecting no-pain scenarios, while it reaches comparable results in detecting weak and severe pain scenarios.
	Address	Palma de Mallorca; Spain; July 2016
	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	AMDO
	Notes	HUPBA;MILAB			Approved	no
	Call Number	Admin @ si @ LNM2016			Serial	2847
Permanent link to this record



	Author	Mark Philip Philipsen; Anders Jorgensen; Thomas B. Moeslund; Sergio Escalera
	Title	RGB-D Segmentation of Poultry Entrails			Type	Conference Article
	Year	2016	Publication	9th Conference on Articulated Motion and Deformable Objects	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Best commercial paper award.
	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	AMDO
	Notes	HuPBA;MILAB			Approved	no
	Call Number	Admin @ si @ PJM2016			Serial	2848
Permanent link to this record



	Author	Antonio Hernandez; Miguel Reyes; Sergio Escalera; Petia Radeva
	Title	Spatio-Temporal GrabCut human segmentation for face and pose recovery			Type	Conference Article
	Year	2010	Publication	IEEE International Workshop on Analysis and Modeling of Faces and Gestures	Abbreviated Journal
	Volume		Issue		Pages	33–40
	Keywords
	Abstract	In this paper, we present a full-automatic Spatio-Temporal GrabCut human segmentation methodology. GrabCut initialization is performed by a HOG-based subject detection, face detection, and skin color model for seed initialization. Spatial information is included by means of Mean Shift clustering whereas temporal coherence is considered by the historical of Gaussian Mixture Models. Moreover, human segmentation is combined with Shape and Active Appearance Models to perform full face and pose recovery. Results over public data sets as well as proper human action base show a robust segmentation and recovery of both face and pose using the presented methodology.
	Address	San Francisco; CA; USA; June 2010
	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	2160-7508	ISBN	978-1-4244-7029-7	Medium
	Area		Expedition		Conference	AMFG
	Notes	MILAB;HUPBA			Approved	no
	Call Number	BCNPCL @ bcnpcl @ HRE2010			Serial	1362
Permanent link to this record



	Author	Bogdan Raducanu; Fadi Dornaika
	Title	Dynamic Vs. Static Recognition of Facial Expressions			Type	Book Chapter
	Year	2008	Publication	Ambient Intelligence. European Conference	Abbreviated Journal
	Volume	5355	Issue		Pages	13–25
	Keywords
	Abstract
	Address	Nuremberg (Germany)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor	Rabuñal
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	AMI
	Notes	OR; MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ RaD2008			Serial	1035
Permanent link to this record



	Author	Eduardo Tusa; Arash Akbarinia; Raquel Gil Rodriguez; Corina Barbalata
	Title	Real-Time Face Detection and Tracking Utilising OpenMP and ROS			Type	Conference Article
	Year	2015	Publication	3rd Asia-Pacific Conference on Computer Aided System Engineering	Abbreviated Journal
	Volume		Issue		Pages	179 - 184
	Keywords	RGB-D; Kinect; Human Detection and Tracking; ROS; OpenMP
	Abstract	The first requisite of a robot to succeed in social interactions is accurate human localisation, i.e. subject detection and tracking. Later, it is estimated whether an interaction partner seeks attention, for example by interpreting the position and orientation of the body. In computer vision, these cues usually are obtained in colour images, whose qualities are degraded in ill illuminated social scenes. In these scenarios depth sensors offer a richer representation. Therefore, it is important to combine colour and depth information. The second aspect that plays a fundamental role in the acceptance of social robots is their real-time-ability. Processing colour and depth images is computationally demanding. To overcome this we propose a parallelisation strategy of face detection and tracking based on two different architectures: message passing and shared memory. Our results demonstrate high accuracy in low computational time, processing nine times more number of frames in a parallel implementation. This provides a real-time social robot interaction.
	Address	Quito; Ecuador; July 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	APCASE
	Notes	NEUROBIT			Approved	no
	Call Number	Admin @ si @ TAG2015			Serial	2659
Permanent link to this record



	Author	Jürgen Brauer; Wenjuan Gong; Jordi Gonzalez; Michael Arens
	Title	On the Effect of Temporal Information on Monocular 3D Human Pose Estimation			Type	Conference Article
	Year	2011	Publication	2nd IEEE International Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Streams	Abbreviated Journal
	Volume		Issue		Pages	906 - 913
	Keywords
	Abstract	We address the task of estimating 3D human poses from monocular camera sequences. Many works make use of multiple consecutive frames for the estimation of a 3D pose in a frame. Although such an approach should ease the pose estimation task substantially since multiple consecutive frames allow to solve for 2D projection ambiguities in principle, it has not yet been investigated systematically how much we can improve the 3D pose estimates when using multiple consecutive frames opposed to single frame information. In this paper we analyze the difference in quality of 3D pose estimates based on different numbers of consecutive frames from which 2D pose estimates are available. We validate the use of temporal information on two major different approaches for human pose estimation – modeling and learning approaches. The results of our experiments show that both learning and modeling approaches benefit from using multiple frames opposed to single frame input but that the benefit is small when the 2D pose estimates show a high quality in terms of precision.
	Address	Barcelona
	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	ARTEMIS
	Notes	ISE			Approved	no
	Call Number	Admin @ si @BGG 2011			Serial	1860
Permanent link to this record