Publicacions CVC -- Query Results

	Publicacions CVC Home \| Show All \| Simple Search \| Advanced Search \| Add Record \| Import	Login Quick Search: Field: contains: ...
	196–210 of 225 records found matching your query (RSS \| history):

Search & Display Options

Select All Deselect All

[1–10] << 11 12 13 14 15 >>

List View

Citations

Details

	Records
	Author	Carles Fernandez; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca
	Title	Towards Ontological Cognitive System			Type	Book Chapter
	Year	2013	Publication	Topics in Medical Image Processing and Computational Vision	Abbreviated Journal
	Volume	8	Issue		Pages	87-99
	Keywords
	Abstract	The increasing ubiquitousness of digital information in our daily lives has positioned video as a favored information vehicle, and given rise to an astonishing generation of social media and surveillance footage. This raises a series of technological demands for automatic video understanding and management, which together with the compromising attentional limitations of human operators, have motivated the research community to guide its steps towards a better attainment of such capabilities. As a result, current trends on cognitive vision promise to recognize complex events and self-adapt to different environments, while managing and integrating several types of knowledge. Future directions suggest to reinforce the multi-modal fusion of information sources and the communication with end-users.
	Address
	Corporate Author				Thesis
	Publisher	Springer Netherlands	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2212-9391	ISBN	978-94-007-0725-2	Medium
	Area		Expedition		Conference
	Notes	ISE; 605.203; 302.018; 600.049			Approved	no
	Call Number	Admin @ si @ FGT2013			Serial	2287
Permanent link to this record



	Author	Jun Wan; Guodong Guo; Sergio Escalera; Hugo Jair Escalante; Stan Z Li
	Title	Best Solutions Proposed in the Context of the Face Anti-spoofing Challenge Series			Type	Book Chapter
	Year	2023	Publication	Advances in Face Presentation Attack Detection	Abbreviated Journal
	Volume		Issue		Pages	37–78
	Keywords
	Abstract	The PAD competitions we organized attracted more than 835 teams from home and abroad, most of them from the industry, which shows that the topic of face anti-spoofing is closely related to daily life, and there is an urgent need for advanced algorithms to solve its application needs. Specifically, the Chalearn LAP multi-modal face anti-spoofing attack detection challenge attracted more than 300 teams for the development phase with a total of 13 teams qualifying for the final round; the Chalearn Face Anti-spoofing Attack Detection Challenge attracted 340 teams in the development stage, and finally, 11 and 8 teams have submitted their codes in the single-modal and multi-modal face anti-spoofing recognition challenges, respectively; the 3D High-Fidelity Mask Face Presentation Attack Detection Challenge attracted 195 teams for the development phase with a total of 18 teams qualifying for the final round. All the results were verified and re-run by the organizing team, and the results were used for the final ranking. In this chapter, we briefly the methods developed by the teams participating in each competition, and introduce the algorithm details of the top-three ranked teams in detail.
	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	HUPBA			Approved	no
	Call Number	Admin @ si @ WGE2023d			Serial	3958
Permanent link to this record



	Author	Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez
	Title	Trajectory-Based Abnormality Categorization for Learning Route Patterns in Surveillance			Type	Book Chapter
	Year	2012	Publication	Detection and Identification of Rare Audiovisual Cues, Studies in Computational Intelligence	Abbreviated Journal
	Volume	384	Issue	3	Pages	87-95
	Keywords
	Abstract	The recognition of abnormal behaviors in video sequences has raised as a hot topic in video understanding research. Particularly, an important challenge resides on automatically detecting abnormality. However, there is no convention about the types of anomalies that training data should derive. In surveillance, these are typically detected when new observations differ substantially from observed, previously learned behavior models, which represent normality. This paper focuses on properly defining anomalies within trajectory analysis: we propose a hierarchical representation conformed by Soft, Intermediate, and Hard Anomaly, which are identified from the extent and nature of deviation from learned models. Towards this end, a novel Gaussian Mixture Model representation of learned route patterns creates a probabilistic map of the image plane, which is applied to detect and classify anomalies in real-time. Our method overcomes limitations of similar existing approaches, and performs correctly even when the tracking is affected by different sources of noise. The reliability of our approach is demonstrated experimentally.
	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	1860-949X	ISBN	978-3-642-24033-1	Medium
	Area		Expedition		Conference
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ BFR2012			Serial	2062
Permanent link to this record



	Author	Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti
	Title	Symbol recognition: current advances and perspectives			Type	Book Chapter
	Year	2002	Publication	Graphics Recognition Algorithms And Applications	Abbreviated Journal	LNCS
	Volume	2390	Issue		Pages	104-128
	Keywords
	Abstract	The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content.
	Address	London, UK
	Corporate Author				Thesis
	Publisher	Springer-Verlag	Place of Publication		Editor	Dorothea Blostein and Young- Bin Kwon
	Language		Summary Language		Original Title
	Series Editor		Series Title	Lecture Notes in Computer Science	Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	3-540-44066-6	Medium
	Area		Expedition		Conference	GREC
	Notes	DAG; IAM;			Approved	no
	Call Number	IAM @ iam @ LVS2002			Serial	1572
Permanent link to this record



	Author	C. Alejandro Parraga
	Title	Color Vision, Computational Methods for			Type	Book Chapter
	Year	2014	Publication	Encyclopedia of Computational Neuroscience	Abbreviated Journal
	Volume		Issue		Pages	1-11
	Keywords	Color computational vision; Computational neuroscience of color
	Abstract	The study of color vision has been aided by a whole battery of computational methods that attempt to describe the mechanisms that lead to our perception of colors in terms of the information-processing properties of the visual system. Their scope is highly interdisciplinary, linking apparently dissimilar disciplines such as mathematics, physics, computer science, neuroscience, cognitive science, and psychology. Since the sensation of color is a feature of our brains, computational approaches usually include biological features of neural systems in their descriptions, from retinal light-receptor interaction to subcortical color opponency, cortical signal decoding, and color categorization. They produce hypotheses that are usually tested by behavioral or psychophysical experiments.
	Address
	Corporate Author				Thesis
	Publisher	Springer-Verlag Berlin Heidelberg	Place of Publication		Editor	Dieter Jaeger; Ranu Jung
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-4614-7320-6	Medium
	Area		Expedition		Conference
	Notes	CIC; 600.074			Approved	no
	Call Number	Admin @ si @ Par2014			Serial	2512
Permanent link to this record



	Author	F.Guirado; Ana Ripoll; C.Roig; Aura Hernandez-Sabate; Emilio Luque
	Title	Exploiting Throughput for Pipeline Execution in Streaming Image Processing Applications			Type	Book Chapter
	Year	2006	Publication	Euro-Par 2006 Parallel Processing	Abbreviated Journal	LNCS
	Volume	4128	Issue		Pages	1095-1105
	Keywords	12th International Euro–Par Conference
	Abstract	There is a large range of image processing applications that act on an input sequence of image frames that are continuously received. Throughput is a key performance measure to be optimized when execu- ting them. In this paper we propose a new task replication methodology for optimizing throughput for an image processing application in the field of medicine. The results show that by applying the proposed methodo- logy we are able to achieve the desired throughput in all cases, in such a way that the input frames can be processed at any given rate.
	Address
	Corporate Author				Thesis
	Publisher	Springer-Verlag Berlin Heidelberg	Place of Publication	Dresden, Germany (European Union)	Editor	UAB; W, E.N.; et al.
	Language		Summary Language		Original Title
	Series Editor		Series Title	Lecture Notes In Computer Science	Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	Euro–Par
	Notes	IAM			Approved	no
	Call Number	IAM @ iam @ GRR2006a			Serial	1542
Permanent link to this record



	Author	Hans Stadthagen-Gonzalez; Luis Lopez; M. Carmen Parafita; C. Alejandro Parraga
	Title	Using two-alternative forced choice tasks and Thurstone law of comparative judgments for code-switching research			Type	Book Chapter
	Year	2018	Publication	Linguistic Approaches to Bilingualism	Abbreviated Journal
	Volume		Issue		Pages	67-97
	Keywords	two-alternative forced choice and Thurstone's law; acceptability judgment; code-switching
	Abstract	This article argues that 2-alternative forced choice tasks and Thurstone’s law of comparative judgments (Thurstone, 1927) are well suited to investigate code-switching competence by means of acceptability judgments. We compare this method with commonly used Likert scale judgments and find that the 2-alternative forced choice task provides granular details that remain invisible in a Likert scale experiment. In order to compare and contrast both methods, we examined the syntactic phenomenon usually referred to as the Adjacency Condition (AC) (apud Stowell, 1981), which imposes a condition of adjacency between verb and object. Our interest in the AC comes from the fact that it is a subtle feature of English grammar which is absent in Spanish, and this provides an excellent springboard to create minimal code-switched pairs that allow us to formulate a clear research question that can be tested using both methods.
	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	NEUROBIT; no menciona			Approved	no
	Call Number	Admin @ si @ SLP2018			Serial	2994
Permanent link to this record



	Author	Fadi Dornaika; Bogdan Raducanu
	Title	Subtle Facial Expression Recognition in Still Images and Videos			Type	Book Chapter
	Year	2011	Publication	Advances in Face Image Analysis: Techniques and Technologies	Abbreviated Journal
	Volume		Issue	14	Pages	259-277
	Keywords
	Abstract	This chapter addresses the recognition of basic facial expressions. It has three main contributions. First, the authors introduce a view- and texture independent schemes that exploits facial action parameters estimated by an appearance-based 3D face tracker. they represent the learned facial actions associated with different facial expressions by time series. Two dynamic recognition schemes are proposed: (1) the first is based on conditional predictive models and on an analysis-synthesis scheme, and (2) the second is based on examples allowing straightforward use of machine learning approaches. Second, the authors propose an efficient recognition scheme based on the detection of keyframes in videos. Third, the authors compare the dynamic scheme with a static one based on analyzing individual snapshots and show that in general the former performs better than the latter. The authors then provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM).
	Address
	Corporate Author				Thesis
	Publisher	IGI-Global	Place of Publication	New York, USA	Editor	Yu-Jin Zhang
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-6152-0991-0	Medium
	Area		Expedition		Conference
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ DoR2011			Serial	1751
Permanent link to this record



	Author	Angel Sappa; David Geronimo; Fadi Dornaika; Mohammad Rouhani; Antonio Lopez
	Title	Moving object detection from mobile platforms using stereo data registration			Type	Book Chapter
	Year	2012	Publication	Computational Intelligence paradigms in advanced pattern classification	Abbreviated Journal
	Volume	386	Issue		Pages	25-37
	Keywords	pedestrian detection
	Abstract	This chapter describes a robust approach for detecting moving objects from on-board stereo vision systems. It relies on a feature point quaternion-based registration, which avoids common problems that appear when computationally expensive iterative-based algorithms are used on dynamic environments. The proposed approach consists of three main stages. Initially, feature points are extracted and tracked through consecutive 2D frames. Then, a RANSAC based approach is used for registering two point sets, with known correspondences in the 3D space. The computed 3D rigid displacement is used to map two consecutive 3D point clouds into the same coordinate system by means of the quaternion method. Finally, moving objects correspond to those areas with large 3D registration errors. Experimental results show the viability of the proposed approach to detect moving objects like vehicles or pedestrians in different urban scenarios.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor	Marek R. Ogiela; Lakhmi C. Jain
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1860-949X	ISBN	978-3-642-24048-5	Medium
	Area		Expedition		Conference
	Notes	ADAS			Approved	no
	Call Number	Admin @ si @ SGD2012			Serial	2061
Permanent link to this record



	Author	David Geronimo; Angel Sappa; Antonio Lopez
	Title	Stereo-based Candidate Generation for Pedestrian Protection Systems			Type	Book Chapter
	Year	2010	Publication	Binocular Vision: Development, Depth Perception and Disorders	Abbreviated Journal
	Volume		Issue	9	Pages	189–208
	Keywords	Pedestrian Detection
	Abstract	This chapter describes a stereo-based algorithm that provides candidate image windows to a latter 2D classification stage in an on-board pedestrian detection system. The proposed algorithm, which consists of three stages, is based on the use of both stereo imaging and scene prior knowledge (i.e., pedestrians are on the ground) to reduce the candidate searching space. First, a successful road surface fitting algorithm provides estimates on the relative ground-camera pose. This stage directs the search toward the road area thus avoiding irrelevant regions like the sky. Then, three different schemes are used to scan the estimated road surface with pedestrian-sized windows: (a) uniformly distributed through the road surface (3D); (b) uniformly distributed through the image (2D); (c) not uniformly distributed but according to a quadratic function (combined 2D-3D). Finally, the set of candidate windows is reduced by analyzing their 3D content. Experimental results of the proposed algorithm, together with statistics of searching space reduction are provided.
	Address
	Corporate Author				Thesis
	Publisher	NOVA Publishers	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			Approved	no
	Call Number	ADAS @ adas @ GSL2010			Serial	1301
Permanent link to this record



	Author	Josep Llados; Marçal Rusiñol
	Title	Graphics Recognition Techniques			Type	Book Chapter
	Year	2014	Publication	Handbook of Document Image Processing and Recognition	Abbreviated Journal
	Volume	D	Issue		Pages	489-521
	Keywords	Dimension recognition; Graphics recognition; Graphic-rich documents; Polygonal approximation; Raster-to-vector conversion; Texture-based primitive extraction; Text-graphics separation
	Abstract	This chapter describes the most relevant approaches for the analysis of graphical documents. The graphics recognition pipeline can be splitted into three tasks. The low level or lexical task extracts the basic units composing the document. The syntactic level is focused on the structure, i.e., how graphical entities are constructed, and involves the location and classification of the symbols present in the document. The third level is a functional or semantic level, i.e., it models what the graphical symbols do and what they mean in the context where they appear. This chapter covers the lexical level, while the next two chapters are devoted to the syntactic and semantic level, respectively. The main problems reviewed in this chapter are raster-to-vector conversion (vectorization algorithms) and the separation of text and graphics components. The research and industrial communities have provided standard methods achieving reasonable performance levels. Hence, graphics recognition techniques can be considered to be in a mature state from a scientific point of view. Additionally this chapter provides insights on some related problems, namely, the extraction and recognition of dimensions in engineering drawings, and the recognition of hatched and tiled patterns. Both problems are usually associated, even integrated, in the vectorization process.
	Address
	Corporate Author				Thesis
	Publisher	Springer London	Place of Publication		Editor	D. Doermann; K. Tombre
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-0-85729-858-4	Medium
	Area		Expedition		Conference
	Notes	DAG; 600.077			Approved	no
	Call Number	Admin @ si @ LlR2014			Serial	2380
Permanent link to this record



	Author	Henry Velesaca; Patricia Suarez; Dario Carpio; Rafael E. Rivadeneira; Angel Sanchez; Angel Morera
	Title	Video Analytics in Urban Environments: Challenges and Approaches			Type	Book Chapter
	Year	2022	Publication	ICT Applications for Smart Cities	Abbreviated Journal
	Volume	224	Issue		Pages	101-121
	Keywords
	Abstract	This chapter reviews state-of-the-art approaches generally present in the pipeline of video analytics on urban scenarios. A typical pipeline is used to cluster approaches in the literature, including image preprocessing, object detection, object classification, and object tracking modules. Then, a review of recent approaches for each module is given. Additionally, applications and datasets generally used for training and evaluating the performance of these approaches are included. This chapter does not pretend to be an exhaustive review of state-of-the-art video analytics in urban environments but rather an illustration of some of the different recent contributions. The chapter concludes by presenting current trends in video analytics in the urban scenario field.
	Address	September 2022
	Corporate Author				Thesis
	Publisher	Springer	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	ISRL
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-031-06306-0	Medium
	Area		Expedition		Conference
	Notes	MSIAU; MACO			Approved	no
	Call Number	Admin @ si @ VSC2022			Serial	3811
Permanent link to this record



	Author	Jorge Charco; Angel Sappa; Boris X. Vintimilla; Henry Velesaca
	Title	Human Body Pose Estimation in Multi-view Environments			Type	Book Chapter
	Year	2022	Publication	ICT Applications for Smart Cities. Intelligent Systems Reference Library	Abbreviated Journal
	Volume	224	Issue		Pages	79-99
	Keywords
	Abstract	This chapter tackles the challenging problem of human pose estimation in multi-view environments to handle scenes with self-occlusions. The proposed approach starts by first estimating the camera pose—extrinsic parameters—in multi-view scenarios; due to few real image datasets, different virtual scenes are generated by using a special simulator, for training and testing the proposed convolutional neural network based approaches. Then, these extrinsic parameters are used to establish the relation between different cameras into the multi-view scheme, which captures the pose of the person from different points of view at the same time. The proposed multi-view scheme allows to robustly estimate human body joints’ position even in situations where they are occluded. This would help to avoid possible false alarms in behavioral analysis systems of smart cities, as well as applications for physical therapy, safe moving assistance for the elderly among other. The chapter concludes by presenting experimental results in real scenes by using state-of-the-art and the proposed multi-view approaches.
	Address	September 2022
	Corporate Author				Thesis
	Publisher	Springer	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	ISRL
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-031-06306-0	Medium
	Area		Expedition		Conference
	Notes	MSIAU; MACO			Approved	no
	Call Number	Admin @ si @ CSV2022b			Serial	3810
Permanent link to this record



	Author	Josep Llados; Gemma Sanchez; Enric Marti
	Title	A string based method to recognize symbols and structural textures in architectural plans			Type	Book Chapter
	Year	1998	Publication	Graphics Recognition Algorithms and Systems Second International Workshop, GREC' 97 Nancy, France, August 22–23, 1997 Selected Papers	Abbreviated Journal	LNCS
	Volume	1389	Issue	1998	Pages	91-103
	Keywords
	Abstract	This paper deals with the recognition of symbols and structural textures in architectural plans using string matching techniques. A plan is represented by an attributed graph whose nodes represent characteristic points and whose edges represent segments. Symbols and textures can be seen as a set of regions, i.e. closed loops in the graph, with a particular arrangement. The search for a symbol involves a graph matching between the regions of a model graph and the regions of the graph representing the document. Discriminating a texture means a clustering of neighbouring regions of this graph. Both procedures involve a similarity measure between graph regions. A string codification is used to represent the sequence of outlining edges of a region. Thus, the similarity between two regions is defined in terms of the string edit distance between their boundary strings. The use of string matching allows the recognition method to work also under presence of distortion.
	Address
	Corporate Author				Thesis
	Publisher	Springer Link	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title	LNCS	Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG; IAM			Approved	no
	Call Number	IAM @ iam @ SLE1998			Serial	1573
Permanent link to this record



	Author	Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados
	Title	Classification of Administrative Document Images by Logo Identification			Type	Book Chapter
	Year	2014	Publication	Graphics Recognition. Current Trends and Challenges	Abbreviated Journal
	Volume	8746	Issue		Pages	49-58
	Keywords	Administrative Document Classification; Logo Recognition; Logo Spotting
	Abstract	This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier’s graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor	Bart Lamiroy; Jean-Marc Ogier
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-662-44853-3	Medium
	Area		Expedition		Conference
	Notes	DAG; 600.056; 600.045; 605.203; 600.077			Approved	no
	Call Number	Admin @ si @ RPK2014			Serial	2701
Permanent link to this record