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Author Alicia Fornes; Josep Llados; Joana Maria Pujadas-Mora
Title Browsing of the Social Network of the Past: Information Extraction from Population Manuscript Images Type Book Chapter
Year 2020 Publication Handwritten Historical Document Analysis, Recognition, and Retrieval – State of the Art and Future Trends Abbreviated Journal
Volume Issue Pages
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Abstract
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Corporate Author Thesis
Publisher World Scientific Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-981-120-323-7 Medium
Area Expedition Conference
Notes DAG; 600.140; 600.121 Approved no
Call Number Admin @ si @ FLP2020 Serial 3350
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Author Joana Maria Pujadas-Mora; Alicia Fornes; Josep Llados; Gabriel Brea-Martinez; Miquel Valls-Figols
Title The Baix Llobregat (BALL) Demographic Database, between Historical Demography and Computer Vision (nineteenth–twentieth centuries Type Book Chapter
Year 2019 Publication Nominative Data in Demographic Research in the East and the West: monograph Abbreviated Journal
Volume Issue Pages 29-61
Keywords
Abstract The Baix Llobregat (BALL) Demographic Database is an ongoing database project containing individual census data from the Catalan region of Baix Llobregat (Spain) during the nineteenth and twentieth centuries. The BALL Database is built within the project ‘NETWORKS: Technology and citizen innovation for building historical social networks to understand the demographic past’ directed by Alícia Fornés from the Center for Computer Vision and Joana Maria Pujadas-Mora from the Center for Demographic Studies, both at the Universitat Autònoma de Barcelona, funded by the Recercaixa program (2017–2019).
Its webpage is http://dag.cvc.uab.es/xarxes/.The aim of the project is to develop technologies facilitating massive digitalization of demographic sources, and more specifically the padrones (local censuses), in order to reconstruct historical ‘social’ networks employing computer vision technology. Such virtual networks can be created thanks to the linkage of nominative records compiled in the local censuses across time and space. Thus, digitized versions of individual and family lifespans are established, and individuals and families can be located spatially.
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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 978-5-7996-2656-3 Medium
Area Expedition Conference
Notes DAG; 600.121 Approved no
Call Number Admin @ si @ PFL2019 Serial 3351
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Author Estefania Talavera; Alexandre Cola; Nicolai Petkov; Petia Radeva
Title Towards Egocentric Person Re-identification and Social Pattern Analysis. Type Book Chapter
Year 2019 Publication Frontiers in Artificial Intelligence and Applications Abbreviated Journal
Volume 310 Issue Pages 203 - 211
Keywords
Abstract CoRR abs/1905.04073
Wearable cameras capture a first-person view of the daily activities of the camera wearer, offering a visual diary of the user behaviour. Detection of the appearance of people the camera user interacts with for social interactions analysis is of high interest. Generally speaking, social events, lifestyle and health are highly correlated, but there is a lack of tools to monitor and analyse them. We consider that egocentric vision provides a tool to obtain information and understand users social interactions. We propose a model that enables us to evaluate and visualize social traits obtained by analysing social interactions appearance within egocentric photostreams. Given sets of egocentric images, we detect the appearance of faces within the days of the camera wearer, and rely on clustering algorithms to group their feature descriptors in order to re-identify persons. Recurrence of detected faces within photostreams allows us to shape an idea of the social pattern of behaviour of the user. We validated our model over several weeks recorded by different camera wearers. Our findings indicate that social profiles are potentially useful for social behaviour interpretation.
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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 MILAB; no proj Approved no
Call Number Admin @ si @ TCP2019 Serial 3377
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Author Lluis Gomez; Anguelos Nicolaou; Marçal Rusiñol; Dimosthenis Karatzas
Title 12 years of ICDAR Robust Reading Competitions: The evolution of reading systems for unconstrained text understanding Type Book Chapter
Year 2020 Publication Visual Text Interpretation – Algorithms and Applications in Scene Understanding and Document Analysis Abbreviated Journal
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Publisher Springer Place of Publication Editor K. Alahari; C.V. Jawahar
Language Summary Language Original Title
Series Editor Series Title Series on Advances in Computer Vision and Pattern Recognition Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes DAG; 600.121 Approved no
Call Number GNR2020 Serial 3494
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Author Lluis Gomez; Dena Bazazian; Dimosthenis Karatzas
Title Historical review of scene text detection research Type Book Chapter
Year 2020 Publication Visual Text Interpretation – Algorithms and Applications in Scene Understanding and Document Analysis Abbreviated Journal
Volume Issue Pages
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Abstract
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Corporate Author Thesis
Publisher Springer Place of Publication Editor K. Alahari; C.V. Jawahar
Language Summary Language Original Title
Series Editor Series Title Series on Advances in Computer Vision and Pattern Recognition Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes DAG; 600.121 Approved no
Call Number Admin @ si @ GBK2020 Serial 3495
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Author Jon Almazan; Lluis Gomez; Suman Ghosh; Ernest Valveny; Dimosthenis Karatzas
Title WATTS: A common representation of word images and strings using embedded attributes for text recognition and retrieval Type Book Chapter
Year 2020 Publication Visual Text Interpretation – Algorithms and Applications in Scene Understanding and Document Analysis Abbreviated Journal
Volume Issue Pages
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Abstract
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Publisher Springer Place of Publication Editor Analysis”, K. Alahari; C.V. Jawahar
Language Summary Language Original Title
Series Editor Series Title Series on Advances in Computer Vision and Pattern Recognition Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes DAG; 600.121 Approved no
Call Number Admin @ si @ AGG2020 Serial 3496
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Author Patricia Suarez; Angel Sappa; Boris X. Vintimilla
Title Deep learning-based vegetation index estimation Type Book Chapter
Year 2021 Publication Generative Adversarial Networks for Image-to-Image Translation Abbreviated Journal
Volume Issue Pages 205-234
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Abstract Chapter 9
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Publisher Elsevier Place of Publication Editor A.Solanki; A.Nayyar; M.Naved
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MSIAU; 600.122 Approved no
Call Number Admin @ si @ SSV2021a Serial 3578
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Author Debora Gil; Oriol Ramos Terrades; Raquel Perez
Title Topological Radiomics (TOPiomics): Early Detection of Genetic Abnormalities in Cancer Treatment Evolution Type Book Chapter
Year 2021 Publication Extended Abstracts GEOMVAP 2019, Trends in Mathematics 15 Abbreviated Journal
Volume 15 Issue Pages 89–93
Keywords
Abstract Abnormalities in radiomic measures correlate to genomic alterations prone to alter the outcome of personalized anti-cancer treatments. TOPiomics is a new method for the early detection of variations in tumor imaging phenotype from a topological structure in multi-view radiomic spaces.
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Publisher Springer Nature 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 IAM; DAG; 600.120; 600.145; 600.139 Approved no
Call Number Admin @ si @ GRP2021 Serial 3594
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Author Michael Teutsch; Angel Sappa; Riad I. Hammoud
Title Cross-Spectral Image Processing Type Book Chapter
Year 2022 Publication Computer Vision in the Infrared Spectrum. Synthesis Lectures on Computer Vision Abbreviated Journal
Volume Issue Pages 23-34
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Abstract Although this book is on IR computer vision and its main focus lies on IR image and video processing and analysis, a special attention is dedicated to cross-spectral image processing due to the increasing number of publications and applications in this domain. In these cross-spectral frameworks, IR information is used together with information from other spectral bands to tackle some specific problems by developing more robust solutions. Tasks considered for cross-spectral processing are for instance dehazing, segmentation, vegetation index estimation, or face recognition. This increasing number of applications is motivated by cross- and multi-spectral camera setups available already on the market like for example smartphones, remote sensing multispectral cameras, or multi-spectral cameras for automotive systems or drones. In this chapter, different cross-spectral image processing techniques will be reviewed together with possible applications. Initially, image registration approaches for the cross-spectral case are reviewed: the registration stage is the first image processing task, which is needed to align images acquired by different sensors within the same reference coordinate system. Then, recent cross-spectral image colorization approaches, which are intended to colorize infrared images for different applications are presented. Finally, the cross-spectral image enhancement problem is tackled by including guided super resolution techniques, image dehazing approaches, cross-spectral filtering and edge detection. Figure 3.1 illustrates cross-spectral image processing stages as well as their possible connections. Table 3.1 presents some of the available public cross-spectral datasets generally used as reference data to evaluate cross-spectral image registration, colorization, enhancement, or exploitation results.
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Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title SLCV
Series Volume Series Issue Edition
ISSN ISBN 978-3-031-00698-2 Medium
Area Expedition Conference
Notes MSIAU; MACO Approved no
Call Number Admin @ si @ TSH2022b Serial 3805
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Author Michael Teutsch; Angel Sappa; Riad I. Hammoud
Title Detection, Classification, and Tracking Type Book Chapter
Year 2022 Publication Computer Vision in the Infrared Spectrum. Synthesis Lectures on Computer Vision Abbreviated Journal
Volume Issue Pages 35-58
Keywords
Abstract Automatic image and video exploitation or content analysis is a technique to extract higher-level information from a scene such as objects, behavior, (inter-)actions, environment, or even weather conditions. The relevant information is assumed to be contained in the two-dimensional signal provided in an image (width and height in pixels) or the three-dimensional signal provided in a video (width, height, and time). But also intermediate-level information such as object classes [196], locations [197], or motion [198] can help applications to fulfill certain tasks such as intelligent compression [199], video summarization [200], or video retrieval [201]. Usually, videos with their temporal dimension are a richer source of data compared to single images [202] and thus certain video content can be extracted from videos only such as object motion or object behavior. Often, machine learning or nowadays deep learning techniques are utilized to model prior knowledge about object or scene appearance using labeled training samples [203, 204]. After a learning phase, these models are then applied in real world applications, which is called inference.
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Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title SLCV
Series Volume Series Issue Edition
ISSN ISBN 978-3-031-00698-2 Medium
Area Expedition Conference
Notes MSIAU; MACO Approved no
Call Number Admin @ si @ TSH2022c Serial 3806
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Author Michael Teutsch; Angel Sappa; Riad I. Hammoud
Title Image and Video Enhancement Type Book Chapter
Year 2022 Publication Computer Vision in the Infrared Spectrum. Synthesis Lectures on Computer Vision Abbreviated Journal
Volume Issue Pages 9-21
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Abstract Image and video enhancement aims at improving the signal quality relative to imaging artifacts such as noise and blur or atmospheric perturbations such as turbulence and haze. It is usually performed in order to assist humans in analyzing image and video content or simply to present humans visually appealing images and videos. However, image and video enhancement can also be used as a preprocessing technique to ease the task and thus improve the performance of subsequent automatic image content analysis algorithms: preceding dehazing can improve object detection as shown by [23] or explicit turbulence modeling can improve moving object detection as discussed by [24]. But it remains an open question whether image and video enhancement should rather be performed explicitly as a preprocessing step or implicitly for example by feeding affected images directly to a neural network for image content analysis like object detection [25]. Especially for real-time video processing at low latency it can be better to handle image perturbation implicitly in order to minimize the processing time of an algorithm. This can be achieved by making algorithms for image content analysis robust or even invariant to perturbations such as noise or blur. Additionally, mistakes of an individual preprocessing module can obviously affect the quality of the entire processing pipeline.
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Corporate Author Thesis
Publisher Springer 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
Notes MSIAU; MACO Approved no
Call Number Admin @ si @ TSH2022a Serial 3807
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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
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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.
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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
Notes HUPBA Approved no
Call Number Admin @ si @ WGE2023b Serial 3956
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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
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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.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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Notes HUPBA Approved no
Call Number Admin @ si @ WGE2023d Serial 3958
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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
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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
Notes HUPBA Approved no
Call Number Admin @ si @ WGE2023c Serial 3957
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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
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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.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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Area Expedition Conference
Notes DAG Approved no
Call Number Admin @ si @ MFK2024 Serial 4020
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