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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 (up)
Notes MSIAU; MACO Approved no
Call Number Admin @ si @ VSC2022 Serial 3811
Permanent link to this record
 
 
Author Victoria Ruiz; Angel Sanchez; Jose F. Velez; Bogdan Raducanu
Title Waste Classification with Small Datasets and Limited Resources Type Book Chapter
Year 2022 Publication ICT Applications for Smart Cities. Intelligent Systems Reference Library Abbreviated Journal
Volume 224 Issue Pages 185-203
Keywords
Abstract Automatic waste recycling has become a very important societal challenge nowadays, raising people’s awareness for a cleaner environment and a more sustainable lifestyle. With the transition to Smart Cities, and thanks to advanced ICT solutions, this problem has received a new impulse. The waste recycling focus has shifted from general waste treating facilities to an individual responsibility, where each person should become aware of selective waste separation. The surge of the mobile devices, accompanied by a significant increase in computation power, has potentiated and facilitated this individual role. An automated image-based waste classification mechanism can help with a more efficient recycling and a reduction of contamination from residuals. Despite the good results achieved with the deep learning methodologies for this task, the Achille’s heel is that they require large neural networks which need significant computational resources for training and therefore are not suitable for mobile devices. To circumvent this apparently intractable problem, we will rely on knowledge distillation in order to transfer the network’s knowledge from a larger network (called ‘teacher’) to a smaller, more compact one, (referred as ‘student’) and thus making it possible the task of image classification on a device with limited resources. For evaluation, we considered as ‘teachers’ large architectures such as InceptionResNet or DenseNet and as ‘students’, several configurations of the MobileNets. We used the publicly available TrashNet dataset to demonstrate that the distillation process does not significantly affect system’s performance (e.g. classification accuracy) of the student network.
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 (up)
Notes LAMP Approved no
Call Number Admin @ si @ Serial 3813
Permanent link to this record
 
 
Author Jun Wan; Guodong Guo; Sergio Escalera; Hugo Jair Escalante; Stan Z Li
Title Face Presentation Attack Detection (PAD) Challenges Type Book Chapter
Year 2023 Publication Advances in Face Presentation Attack Detection Abbreviated Journal
Volume Issue Pages 17–35
Keywords
Abstract In recent years, the security of face recognition systems has been increasingly threatened. Face Anti-spoofing (FAS) is essential to secure face recognition systems primarily from various attacks. In order to attract researchers and push forward the state of the art in Face Presentation Attack Detection (PAD), we organized three editions of Face Anti-spoofing Workshop and Competition at CVPR 2019, CVPR 2020, and ICCV 2021, which have attracted more than 800 teams from academia and industry, and greatly promoted the algorithms to overcome many challenging problems. In this chapter, we introduce the detailed competition process, including the challenge phases, timeline and evaluation metrics. Along with the workshop, we will introduce the corresponding dataset for each competition including data acquisition details, data processing, statistics, and evaluation protocol. Finally, we provide the available link to download the datasets used in the challenges.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title SLCV
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference (up)
Notes HUPBA Approved no
Call Number Admin @ si @ WGE2023b Serial 3956
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 (up)
Notes HUPBA Approved no
Call Number Admin @ si @ WGE2023d Serial 3958
Permanent link to this record
 
 
Author Jun Wan; Guodong Guo; Sergio Escalera; Hugo Jair Escalante; Stan Z Li
Title Face Anti-spoofing Progress Driven by Academic Challenges Type Book Chapter
Year 2023 Publication Advances in Face Presentation Attack Detection Abbreviated Journal
Volume Issue Pages 1–15
Keywords
Abstract With the ubiquity of facial authentication systems and the prevalence of security cameras around the world, the impact that facial presentation attack techniques may have is huge. However, research progress in this field has been slowed by a number of factors, including the lack of appropriate and realistic datasets, ethical and privacy issues that prevent the recording and distribution of facial images, the little attention that the community has given to potential ethnic biases among others. This chapter provides an overview of contributions derived from the organization of academic challenges in the context of face anti-spoofing detection. Specifically, we discuss the limitations of benchmarks and summarize our efforts in trying to boost research by the community via the participation in academic challenges
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title SLCV
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference (up)
Notes HUPBA Approved no
Call Number Admin @ si @ WGE2023c Serial 3957
Permanent link to this record
 
 
Author Beata Megyesi; Alicia Fornes; Nils Kopal; Benedek Lang
Title Historical Cryptology Type Book Chapter
Year 2024 Publication Learning and Experiencing Cryptography with CrypTool and SageMath Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Historical cryptology studies (original) encrypted manuscripts, often handwritten sources, produced in our history. These historical sources can be found in archives, often hidden without any indexing and therefore hard to locate. Once found they need to be digitized and turned into a machine-readable text format before they can be deciphered with computational methods. The focus of historical cryptology is not primarily the development of sophisticated algorithms for decipherment, but rather the entire process of analysis of the encrypted source from collection and digitization to transcription and decryption. The process also includes the interpretation and contextualization of the message set in its historical context. There are many challenges on the way, such as mistakes made by the scribe, errors made by the transcriber, damaged pages, handwriting styles that are difficult to interpret, historical languages from various time periods, and hidden underlying language of the message. Ciphertexts vary greatly in terms of their code system and symbol sets used with more or less distinguishable symbols. Ciphertexts can be embedded in clearly written text, or shorter or longer sequences of cleartext can be embedded in the ciphertext. The ciphers used mostly in historical times are substitutions (simple, homophonic, or polyphonic), with or without nomenclatures, encoded as digits or symbol sequences, with or without spaces. So the circumstances are different from those in modern cryptography which focuses on methods (algorithms) and their strengths and assumes that the algorithm is applied correctly. For both historical and modern cryptology, attack vectors outside the algorithm are applied like implementation flaws and side-channel attacks. In this chapter, we give an introduction to the field of historical cryptology and present an overview of how researchers today process historical encrypted sources.
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 (up)
Notes DAG Approved no
Call Number Admin @ si @ MFK2024 Serial 4020
Permanent link to this record
 
 
Author Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru; Miguel Angel Gonzalez Ballester
Title Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs Type Book Chapter
Year 2012 Publication Workshop on Computational and Clinical Applications in Abdominal Imaging Abbreviated Journal
Volume 7029 Issue Pages 223–230
Keywords medial manifolds, abdomen.
Abstract Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D
objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial
manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our
method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs,
exploring the use of medial manifolds for the representation of multi-organ relations.
Address Toronto; Canada;
Corporate Author Thesis
Publisher Springer Link Place of Publication Berlin Editor H. Yoshida et al
Language English Summary Language English Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-28556-1 Medium
Area Expedition Conference (up) ABDI
Notes IAM;MV Approved no
Call Number IAM @ iam @ VGB2012 Serial 1834
Permanent link to this record
 
 
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 (up) 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 (up) AMDO
Notes ISE Approved no
Call Number ISE @ ise @ CPG2008 Serial 975
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 (up) AMI
Notes OR; MV Approved no
Call Number BCNPCL @ bcnpcl @ RaD2008 Serial 1035
Permanent link to this record
 
 
Author Debora Gil; F. Javier Sanchez; Gloria Fernandez Esparrach; Jorge Bernal
Title 3D Stable Spatio-temporal Polyp Localization in Colonoscopy Videos Type Book Chapter
Year 2015 Publication Computer-Assisted and Robotic Endoscopy. Revised selected papers of Second International Workshop, CARE 2015, Held in Conjunction with MICCAI 2015 Abbreviated Journal
Volume 9515 Issue Pages 140-152
Keywords Colonoscopy, Polyp Detection, Polyp Localization, Region Extraction, Watersheds
Abstract Computational intelligent systems could reduce polyp miss rate in colonoscopy for colon cancer diagnosis and, thus, increase the efficiency of the procedure. One of the main problems of existing polyp localization methods is a lack of spatio-temporal stability in their response. We propose to explore the response of a given polyp localization across temporal windows in order to select
those image regions presenting the highest stable spatio-temporal response.
Spatio-temporal stability is achieved by extracting 3D watershed regions on the
temporal window. Stability in localization response is statistically determined by analysis of the variance of the output of the localization method inside each 3D region. We have explored the benefits of considering spatio-temporal stability in two different tasks: polyp localization and polyp detection. Experimental results indicate an average improvement of 21:5% in polyp localization and 43:78% in polyp detection.
Address
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 (up) CARE
Notes IAM; MV; 600.075 Approved no
Call Number Admin @ si @ GSF2015 Serial 2733
Permanent link to this record
 
 
Author Fernando Vilariño; Petia Radeva
Title Cardiac Segmentation with Discriminant Active Contours Type Book Chapter
Year 2003 Publication Abbreviated Journal
Volume Issue Pages 211–217
Keywords
Abstract Dynamic tracking of heart moving is one relevant target in medical imag- ing and can be helpful for analyzing heart dynamics in the study of several cardiac diseases. For this aim, a previous segmentation problem of such structures is stated, based on certain relevant features (like edges or intensity levels, textures, etc.) Clas- sical active models have been used, but they fail when overlapping structures or not well-defined contours are present. Automatic feature learning systems may be a pow- erful tool. Discriminant active contours present optimal results in this kind of problem. They are a kind of deformable models that converge to an optimal object segmenta- tion that dynamically adapts to the object contour. The feature space is designed from a filter bank in order to guarantee the search and learning of the set of relevant fea- tures for optimal classification on each part of the object. Tracking of target evolution is obtained through the whole set of images, using information from the actual and previous stages. Feedback systems are implemented to guarantee the minimum well- separable classification set in each segmentation step. Our implementation has been proved with several series of Magnetic Resonance with improved results in segmenta- tion in comparison to previous methods.
Address Palma de Mallorca
Corporate Author Thesis
Publisher IOS Press 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 (up) CCIA
Notes MV;MILAB;SIAI Approved no
Call Number BCNPCL @ bcnpcl @ ViR2003; IAM @ iam @ VRa2003 Serial 426
Permanent link to this record
 
 
Author Jaume Garcia; Petia Radeva; Francesc Carreras
Title Combining Spectral and Active Shape methods to Track Tagged MRI Type Book Chapter
Year 2004 Publication Recent Advances in Artificial Intelligence Research and Development Abbreviated Journal
Volume Issue Pages 37-44
Keywords MR; tagged MR; ASM; LV segmentation; motion estimation.
Abstract Tagged magnetic resonance is a very usefull and unique tool that provides a complete local and global knowledge of the left ventricle (LV) motion. In this article we introduce a method capable of tracking and segmenting the LV. Spectral methods are applied in order to obtain the so called HARP images which encode information about movement and are the base for LV point-tracking. For segmentation we use Active Shapes (ASM) that model LV shape variation in order to overcome possible local misplacements of the boundary. We finally show experiments on both synthetic and real data which appear to be very promising.
Address
Corporate Author Thesis
Publisher IOS Press 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 (up) CCIA
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ GRC2004 Serial 1488
Permanent link to this record
 
 
Author Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Carolina Malagelada; Petia Radeva
Title A Machine Learning framework using SOMs: Applications in the Intestinal Motility Assessment Type Book Chapter
Year 2006 Publication 11th Iberoamerican Congress on Pattern Recognition Abbreviated Journal
Volume 4225 Issue Pages 188–197
Keywords
Abstract Small Bowel Motility Assessment by means of Wireless Capsule Video Endoscopy constitutes a novel clinical methodology in which a capsule with a micro-camera attached to it is swallowed by the patient, emitting a RF signal which is recorded as a video of its trip throughout the gut. In order to overcome the main drawbacks associated with this technique -mainly related to the large amount of visualization time required-, our efforts have been focused on the development of a machine learning system, built up in sequential stages, which provides the specialists with the useful part of the video, rejecting those parts not valid for analysis. We successfully used Self Organized Maps in a general semi-supervised framework with the aim of tackling the different learning stages of our system. The analysis of the diverse types of images and the automatic detection of intestinal contractions is performed under the perspective of intestinal motility assessment in a clinical environment.
Address Cancun (Mexico)
Corporate Author Thesis
Publisher Springer Verlag Place of Publication Berlin-Heidelberg Editor J.P. Martinez–Trinidad et al
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area 800 Expedition Conference (up) CIARP06
Notes MV;OR;MILAB;SIAI Approved no
Call Number BCNPCL @ bcnpcl @ VSV2006d; IAM @ iam @ VSV2006e Serial 729
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 (up) Euro–Par
Notes IAM Approved no
Call Number IAM @ iam @ GRR2006a Serial 1542
Permanent link to this record