ACM Journal on

Computing and Cultural Heritage (JOCCH)

Latest Articles

Digital Mont’e Prama

We present and evaluate a scalable interactive system for the exploration of large collections of detailed three-dimensional digital models of sculptures. The system has been applied to the valorization of the Mont’e Prama complex, an extraordinary collection of protostoric Mediterranean sculptures, which depict models of cone-shaped stone... (more)

Interactive 3D Segmentation of Rock-Art by Enhanced Depth Maps and Gradient Preserving Regularization

Petroglyphs (rock engravings) have been pecked and engraved by humans into natural rock surfaces thousands of years ago and are among the oldest... (more)

Analyzing the Decorative Style of 3D Heritage Collections Based on Shape Saliency

As technologies for 3D acquisition become widely available, it is expected that 3D content documenting heritage artifacts will become increasingly... (more)


In Memoriam of David Arnold, founder EiC of JOCCH, see obituary here. David died unexpectedly on the 25th of October 2016.

JOCCH to be indexed by ISI very soon

We are pleased to inform you that JOCCH has been accepted by ISI to be included into the Science Citation Index Expanded and the Arts & Humanities Citation Index. See more information.

JOCCH indexed on SCOPUS

The figures available as of April 2016  are:
- SCImago Journal Rank: 0.437
- Impact per Publication: 0.900
- Source Normalized Impact per Paper: 1.676

For more information on these figures see here.

Call open for the special issue on "Digital Infrastructure for Cultural Heritage" (deadline on the 30th of April 2016). See more information.


ACM is endorsing ORCID, a community-based effort to create a global registry of unique researcher identifiers for the purpose of ensuring proper attribution of works to their creators. JOCCH authors are invited to create an ORCID unique researcher identifier (see at ) and to add this id at submission time.

Impact Factor Update

The journal Impact Factor (IF) is produced by ISI. A pre-condition to the application process is a record of timely publication of journal issues over a two-year period. I am pleased to announce that JOCCH followed a regular publishing schedule from 2012 through 2013 and so the procedure for requesting the ISI IF certification started early 2014. The evaluation period will take approximately two years.
In the meantime, please note that ACM JOCCH is cited and measured in SCImago and in the Elsevier's Journal Metrics system, based on Scopus data.

From Reassembly to Object Completion - A Complete Systems Pipeline

The problem of restoration of broken artefacts, where large parts could be missing, is of high importance in archaeology. The typical manual restoration can become a tedious and error-prone process, which also does not scale well. In recent years, many methods have been proposed for assisting the process, most of which target specialized object types or operate under very strict constraints. We propose a digital shape restoration pipeline consisting of proven, robust methods for automatic fragment reassembly and shape completion of generic three-dimensional objects of arbitrary type. In this pipeline, first we introduce a novel unified approach for handling the reassembly of objects from heavily damaged fragments by exploiting both fracture surfaces and salient features on the intact sides of fragments, when available. Second, we propose an object completion procedure based on generalized symmetries and a complementary part extraction process that is suitable for driving the fabrication of missing geometry. We demonstrate the effectiveness of our approach using real-world fractured objects and software implemented as part of the EU-funded PRESIOUS project, which is also available for download from the project site.

Improving Archaeologists Online Archive Experiences Through User-Centred Design

Traditionally, the preservation of archaeological data has been limited by the cost of materials and the physical space required to store them, but for the last 20 years, increasing amounts of digital data have been generated and stored online. New techniques like digital photography and document scanning have dramatically increased the amount of data that can be retained in digital format, while at the same time reducing the physical cost of production and storage. Vast numbers of hand written notes, grey literature documents, images of assemblages, contexts, and artefacts have been made available online. However, accessing these repositories is not always straightforward. Superficial interaction design, sparsely populated metadata, and heterogeneous schemas may prevent the user from working the data that they need within archaeological archives. In this paper, we present the work of the Digging into Archaeological Data and Image Search Metadata project (DADAISM), a multidisciplinary project that draws together the work of researchers from the fields of archaeology, interaction design, image processing and text mining to create a user centred interactive system that supports archaeologists in their tasks when working with digital image and document archives. By building on the existing broad literature on archive users, and adopting a user centered approach with techniques in contextual design, we designed and evaluated an interactive system that successfully integrates image based retrieval and improved metadata searching to provide access to documents that were previously difficult to search. We also demonstrate that the user-centred design approach has allowed us to acquire new knowledge on how archaeologists enter two distinct phases of work during information seeking tasks, which can be used as inspiration for future interactive systems.

A Web-Based Infrastructure for the Assisted Annotation of Heritage Collections

Annotations provide a valuable perspective on the semantic information present in digital heritage collections, and in recent years theyve been employed in a number of innovative, user-centric techniques that can personalise a users experience of heritage materials, such as by actively adapting exhibits as a user reveals their interests, or by guiding users to explore collections which are meaningfully linked to what they have previously encountered. Despite the captivating opportunities offered by these techniques, collecting annotations for a large heritage collection is no trivial task. A significant amount of work is required to manually annotate large quantities of heritage materials, and automated, computational approaches leave much to be desired regarding the level of insight and semantic richness that they can currently provide. By analysing the emergent relationships between the initial annotations in a collection, we propose a novel metadata-driven algorithm for assisting and augmenting the annotation process. This algorithm, called SAGA (Semantically-Annotated Graph Analysis), allows for semi-automatic annotation, which balances the value of the contributions of human annotators with the time and effort-saving benefits of an automatic, suggestion-driven process. SAGA uses an entity relationship-driven approach to make annotation suggestions. It is used in the context of a web-based infrastructure called SAGE (Semantic Annotation by Group Exploration), a multiagent environment which assists groups of experts in creating comprehensive annotation sets for heritage collections. SAGA and SAGE are evaluated from the perspectives of suggestion accuracy, explicit user acceptance and implicit user acceptance, and demonstrate strong results in each evaluation.

Semi-automatic Construction of Cross-period Thesaurus

A cross-period (diachronic) thesaurus enables users to search for information using modern terminology and obtain semantically related terms from earlier historical periods.The complex task of supporting the construction of a diachronic thesaurus by a domain expert lexicographer has hardly been addressed computationally till now. In this paper, we introduce a semi-automatic iterative Query Expansion (QE) scheme for supporting diachronic thesaurus construction, which identi es candidate related terms based on statistical corpus-based measures. We use ancient-modern period classi cation to increase the performance of the statistical co-occurrence measures and extend our methods to deal with Multi Word Expressions (MWEs). We demonstrate the empirical bene t of our scheme for a Jewish cross-period thesaurus and evaluate its impact on recall and on the e ectiveness of the lexicographer's manual e orts.

Visual Recognition of Ancient Inscriptions using Convolutional Neural Network and Fisher Vector

By bringing together the most prominent European institutions and archives in the field of Classical Latin and Greek epigraphy, the EAGLE project is collecting the vast majority of the surviving Greco-Latin inscriptions into a single readily-searchable database. To retrieve information about ancient inscriptions (or about other artifacts), text-based search engines are typically adopted. These systems require that the users formulate a text query that contains information, as the place where the object was been found or where it is actually located. Conversely, visual search system can be used to provide information to users (as tourist and scholars) in a most intuitive and immediate way: just using an image as query. In this paper, we provide an exhaustive comparison of several approaches for visual recognizing ancient inscriptions in order to find the most prominent approach to search EAGLE repository by using a photo as query. To date, just the Bag-of-(Visual)Words (BoW) and the Vector of Locally Aggregated Descriptors (VLAD) techniques have been already tested on this scenario. Our experiments, conducted on 17,155 photos related to 14,560 inscriptions, showed that BoW and VLAD are outperformed by both Fisher Vector (FV) and Convolutional Neural Networks (CNN) features. More interestingly, combining FV and CNN features into a single image representation allowed us to achieve very high effectiveness by correctly recognizing the query inscription in more than 90% of the cases. Our results suggest that combinations of FV and CNN could be further exploited in order to effectively perform visual retrieval of other kind of objects related to cultural heritage, such as landmarks and monuments.

Automatic Single Page-based Algorithms for Medieval Manuscript Analysis

We propose three automatic algorithms for analyzing digitized medieval manuscripts: text block computation, text line segmentation and special component extraction, by taking advantage of previous clustering algorithms and a template matching technique. These three methods are completely automatic, so that no user intervention or input is required to make them work. Moreover, they are all per-page based; that is, unlike some prior methods--which need a set of pages from the same manuscript for training purposes--they are able to analyze a single page without requiring any additional pages for input, eliminating the need for training on additional pages with similar layout. We extensively evaluated the algorithms on 1771 images of pages of 6 different publicly available historical manuscripts, which differ significantly from each other in terms of layout structure, acquisition resolution, and writing style, etc. The experimental results indicate that they are able to achieve very satisfactory performance, i.e., the average precision and recall values obtained by the text block computation method can reach as high as 98% and 99%, respectively.

Extracting Maya Glyphs from Degraded Ancient Documents via Image Segmentation

We present a system for automatically extracting hieroglyph strokes from images of degraded ancient Maya codices. Our system adopts a region-based image segmentation framework. Multi-resolution super-pixels are first extracted to represent each image. A SVM classifier is used to label each super-pixel region with a probability to belong to foreground glyph strokes. Pixel-wise probability maps from multiple super-pixel resolution scales are aggregated to cope with various stroke widths and background noise. A fully connected Conditional Random Field (CRF) model is then applied to improve the labeling consistency. Segmentation results show that our system preserves delicate local details of the historic Maya glyphs with various stroke widths, and also reduces background noise. As an application, we conduct retrieval experiments using the extracted binary images, to further evaluate our system. Experimental results show that our automatically extracted glyph strokes achieve comparable retrieval results with what was achieved using glyphs manually segmented by epigraphers in our team. Two Maya hieroglyph image datasets are contributed, which can be used as image segmentation and shape analysis benchmarks, and also to study the ancient Maya writing system.

A Knowledge Management Architecture For Digital Cultural Heritage

The increasing demand of technological facilities for galleries, museums and archives led to the need of designing practical and effective solutions for managing the digital life-cycle of cultural heritage collections. These facilities have to support users in addressing several challenges directly related to the creation, management, preservation, and visualization of digital collections. Such challenges include, for example, the support for a collaborative management of the produced information, their curation from a multilingual perspective in order to break the language barriers and make collections available to different stakeholders, and to provide services for exposing structured version of data to both users and machines. Platforms satisfying all these requirements have to support curators activities and, at the same time, to provide facilities for engaging the virtual consumers of the produced data. In this paper, we propose a description of an abstract architecture for managing digital collections built upon a set of components, services, and APIs able to address the challenges mentioned above. Then, an instantiation of this architecture is discussed, as well as the presentation of a use case concerning the management of a digital archive of verbo-visual art. Lessons learned from this experience are reported in order to outline future activities.


Ancient paintings can provide valuable information for historians and archeologist to study the history and humanity at the corresponding eras. How to determine the era in which a painting was created is a critical problem, since the topic of a painting can not be used as an effective basis without an era label. To address this problem, this paper proposes a novel computational method by using multi-view local color features extracted from the paintings. Firstly, we extract the multi-view local color features for all training images using a novel descriptor named Affine Lab-SIFT. Then, we can learn the codebook from all these features by K-mean clustering. Afterwords, we create feature histogram for each image in the form of bag-of-visual-words and use a supervised fashion to train a classifier, which is used for further painting classification. Experimental results from two total different datasets show the effect of the proposed classification system and the advantage of the proposed features, especially in the case of small-size training samples.

Big Data meets Digital Cultural Heritage: design and implementation of SCRABS

Information and Communication technologies have radically changed the modern Cultural Heritage domain, from traditional information management system associated to cultural artifacts, to complex system containing huge quantity of informations extracted from a variety of data sources (such as Sensor Networks, Social Networks, Digital Libraries, Multimedia Collections, Web Data Service), thus providing a great number of applications that enhance the users' experience. In this paper we describe SCRABS , a Smart Context-awaRe Browsing assistant for cultural EnvironmentS, a system for managing and context-driven browsing of cultural environments, developed during the Cultural heritage Information Systems (CHIS) national project and promoted by DATABENC, the Cultural Heritage Technological District of Campania Region, Italia. SCRABS has been designed on the top of a BIG DATA technological stack, and is the results of a multidisciplinary project carried out from Computer Scientists, Archeologists, Architects and Humanities experts. We describe the main ideas beyond the proposed system, showing how it is useful in some real application scenarios located in the Paestum Archeologica Sites.

Digging Wikipedia. The online encyclopedia as digital cultural heritage gateway and site

The online encyclopedia Wikipedia is both a cultural reference to store, refer to, and organize digitized and digital information as well as a key contemporary digital heritage endeavor in itself. Capitalizing on this dual nature of the project, this article introduces Wikipedia as a digital gateway to and site of active engagement with cultural heritage. We have developed the open source and freely available analysis architecture Contropedia to examine already existing volunteer user-generated participation around cultural heritage and to promote further engagement with it. Conceptually, we employ the notion of memory work as it helps to employ Wikipedias articles, edit histories, and discussion pages as a rich resource to study how cultural heritage is received and (re-)worked in and across different languages and cultures. Contropedias architecture allows for the study of the negotiations around and appreciation of cultural heritage without assuming an unchallenged and universal understanding of cultural heritage. The analysis facilitated by Contropedia thus sheds light on the contentious articulation of perspectives on tangible and intangible heritage grounded by conflicting conceptions of events, ideas, places, or persons. Technologically, Contropedia combines techniques based on mining article edit histories and analyzing discussion patterns in talk pages to identify and visualize heritage-related disputes within an article, and to compare these across language versions. In terms of digital heritage, Contropedia presents a powerful tool that opens up a core resource to cultural heritage studies. Moreover, it can form part of a conceptually grounded, technically advanced, and practically enrolled infrastructure for public education that opens up the dynamic formation of both knowledge about cultural heritage and new forms of digital cultural heritage that show a considerable amount of friction.

Ubiquitous Access to Digital Cultural Heritage

The digitization initiatives in the past decades have lead to a tremendous increase of digitized objects in the cultural heritage domain. Although digitally available, these objects are often not easily accessible for interested users because of the distributed allocation of the content in different repositories and the variety in data structure and standards. When users search for cultural content they first need to identify the specific repository and then need to know how to search within this platform (e.g., usage of specific vocabulary). The goal of the EEXCESS project is to design and implement an infrastructure that enables ubiquitous access to digital cultural heritage data. In addition, cultural content should be made available in the channels users habitually visit and be tailored to their current context without the need to manually search multiple portals or content repositories. In order to realize this goal open-source software components and services have been developed which can either be used as an integrated infrastructure or as modular components suitable to be integrated in other products and services. The EEXCESS modules and components comprise (i) web-based context detection, (ii) information retrieval-based, federated content aggregation, (iii) metadata definition and mapping, and (iv) a component responsible for privacy-preservation. Various applications have been realized based on these components that bring cultural content to the user in content consumption and content creation scenarios. Content consumption is for example realized by a browser extension generating automatic search queries from the current page context and the focus paragraph and presenting related results aggregated from different data providers. A Google Docs add-on allows to retrieve relevant content aggregated from multiple data providers while collaboratively writing a document. These relevant resources then can be included in the current document either as citation, an image or link (with preview), without having to leave disrupt the current writing task for an explicit search in various content providers' portals.

Innovation through Large-scale Integration of Legacy Records: Assessing the ¿Value Added¿ in Cultural Heritage Resources

Using the Chaco Research Archive as a case study, in this paper we discuss the variable scales of intellectual and computational labor embedded in digital curation projects and how these layered processes all add value to digital data. We outline some of the pitfalls of conventional academic metrics for scholarly impact and provide some alternative means to assess the value of digital heritage resources. Lastly, we explore how a focused digital heritage resource can enable vast opportunities for research and foster communities of co-creation.

The European Holocaust Research Infrastructure Portal

The Digital Music Lab: A Big Data Infrastructure for Digital Musicology

In musicology and music research generally, the increasing availability of digital music, storage capacities and computing power both enable and require new and intelligent systems. In the transition from traditional to digital musicology, many techniques and tools have been developed for the analysis of individual pieces of music, but large scale music data that are increasingly becoming available require research methods and systems that work on the collection-level and at scale. Although many relevant algorithms have been developed during the last 15 years of research in Music Information Retrieval, an integrated system that supports large-scale digital musicology research has so far been lacking. In the Digital Music Lab (DML) project, a collaboration between music librarians, musicologists, computer scientists, and human-computer interface specialists, the DML software system has been developed that fills this gap by providing intelligent large-scale music analysis with a user-friendly interactive interface supporting musicologists in their exploration and enquiry. The DML system empowers musicologists by addressing several challenges: distributed processing of audio and other music data, management of the data analysis process and results, remote analysis of data under copyright, logical inference on the extracted information and metadata, and visual web-based interfaces for exploring and querying the music collections. The DML system is scalable and based on Semantic Web technology and integrates into Linked Data with the vision of a distributed system that enabling music research across archives, libraries and other providers of music data. A first DML system prototype has been set up in collaboration with the British Library and I Like Music Ltd. This system has been used to analyse a diverse corpus of currently 250,000 music tracks. In this article we describe the DML system requirements, design, architecture, components, available data sources, explaining their interaction. We report use cases and applications with initial evaluations of the proposed system.

Access to recorded interviews: A research agenda

The arrigo showcase reloaded—towards a sustainable link between 3D and semantics

Research challenges for digital archives of 3D cultural heritage models

IsoCam: Interactive Visual Exploration of Massive Cultural Heritage Models on Large Projection Setups

A taxonomy of visualization strategies for cultural heritage applications

Dynamic shading enhancement for reflectance transformation imaging

Modeling visitors' profiles: A study to investigate adaptation aspects for museum learning technologies

Using ontological and document similarity to estimate museum exhibit relatedness

A visitor's guide in an active museum: Presentations, communications, and reflection

A serious game model for cultural heritage


Publication Years 2008-2016
Publication Count 153
Citation Count 273
Available for Download 153
Downloads (6 weeks) 1436
Downloads (12 Months) 10494
Downloads (cumulative) 63735
Average downloads per article 417
Average citations per article 2
First Name Last Name Award
Ugur Gudukbay ACM Senior Member (2008)
Tsvi Kuflik ACM Distinguished Member (2013)
ACM Senior Member (2012)
George Lepouras ACM Senior Member (2008)
Holly E Rushmeier ACM Distinguished Member (2006)

First Name Last Name Paper Counts
Roberto Scopigno 6
Marco Callieri 5
Enrico Gobbetti 5
Matteo Dellepiane 4
Ruggero Pintus 4
Livio Luca 3
Paolo Cignoni 3
Fabio Bettio 3
Fabio Marton 3
Martin Doerr 3
Massimiliano Corsini 3
Christian Breiteneder 2
Nadine Couture 2
Angeliki Antoniou 2
David Mortimore 2
Thomas Funkhouser 2
Alan Chalmers 2
Valentina Fiore 2
Alessandro De Gloria 2
Matthias Zeppelzauer 2
George Lepouras 2
Anke Lüdeling 2
Hijung Shin 2
Lily Diaz 2
Gregory Crane 2
Rudolf Gschwind 2
Marcos Rodriguez 2
Riccardo Berta 2
Nick Corps 2
Carlos Sanchez-Belenguer 2
Volker Settgast 2
Markus Seidl 2
Markku Reunanen 2
Graham Bell 2
Stephen Laycock 2
Dieter Fellner 2
Alberto Villanueva 2
Tim Weyrich 2
Szymon Rusinkiewicz 2
Eduardo Vendrell-Vidal 2
Marco Agus 2
Francesco Bellotti 2
Simon Flöry 1
Øyvind Eide 1
Vinay Das 1
Daryl Baldwin 1
Ruth Tringham 1
Lukas Rosenthaler 1
Wei Luo 1
Moshe Ben-Ezra 1
Michael Brown 1
Kenneth Steiglitz 1
Georg Poier 1
Torsten Ullrich 1
Fermin Gomez 1
Andreas Aristidou 1
Pierre Drap 1
Lior Shamir 1
Josef Froschauer 1
Dieter Merkl 1
Yiting Huang 1
Zhongke Wu 1
Maria Zapata 1
Emilia GóMez 1
Niels Raes 1
Patrick Brundell 1
Steve Benford 1
C Chaffardon 1
Stefano Paci 1
Elvira Aura-Castro 1
Amir Zeldes 1
Raphaële Héno 1
Gianvito Pio 1
David Mimno 1
Daniel Isemann 1
Charalambos Poullis 1
Naokazu Yokoya 1
Luciana Martins 1
Jane Hunter 1
David Tidmarsh 1
Antonio Pizzo 1
Bernard Tiddeman 1
M Vetter 1
Frank Bauer 1
Mona Hess 1
Stuart Robson 1
Margaret Serpico 1
Michela Mortara 1
Lauto Magnani 1
Emilio Merella 1
Chiara Leoni 1
Roberto Turco 1
Maarten Heerlien 1
Andreas Reichinger 1
Nadine Kroher 1
José Díaz-Báñez 1
Kirsten Van Hulsen 1
Stéphane Marchand-Maillet 1
S Siano 1
S May 1
Irene Rubino 1
Cecilia Pisa 1
I Finkel 1
Willemijn Heeren 1
Stefano Capuzzi 1
Alexandra Poulovassilis 1
Chihhao Yu 1
Vincenzo Lombardo 1
Raimund Karl 1
Seren Griffiths 1
Greta Franzini 1
Anna Sivula 1
Michael Weinmann 1
Karl Grieser 1
Timothy Baldwin 1
Tsvi Kuflik 1
Elisa Bertino 1
Teresa Romao 1
Alina Glushkova 1
Petros Daras 1
Constantin Papaodysseus 1
Dimitris Arabadjis 1
Michail Panagopoulos 1
Nikolaos Aletras 1
Gianpaolo Palma 1
Deyun Zhang 1
Yifeng Fan 1
René Berndt 1
Francis Schmitt 1
Douglas Troy 1
Özgür Ulusoy 1
Guido Brunnett 1
Yiping Hung 1
Albert Kavelar 1
Klaus Riede 1
Franciska De Jong 1
Masayuki Kanbara 1
Kirk Woolford 1
Xuan Wang 1
Andrew Wilson 1
Jacob Madsen 1
Christian Siegl 1
Hera Almpanoudi 1
Robert Sitnik 1
Maria Moritz 1
Jaakko Suominen 1
Christopher Schwartz 1
Patrick Marais 1
Sadek Jbara 1
Eva Pietroni 1
A Miranda 1
Jérémy Laviole 1
Xavier Granier 1
S Baldissini 1
Kaizhong Zhang 1
Michael Hofer 1
Stefano Girardi 1
Alessandro Rizzi 1
Uğur Güdükbay 1
Claus Fleischer 1
Isaac Besora 1
Rachid Thami 1
Efstathios Stavrakis 1
Yiorgos Chrysanthou 1
Zhi Gao 1
Claudio Gennaro 1
Michael Kolomenkin 1
Ayellet Tal 1
Angelos Yannopoulos 1
Chaya Liebeskind 1
Jonathan Schler 1
Wei Ma 1
Yizhou Wang 1
César Gonzalez-Perez 1
Xin Ma 1
Wen Gao 1
Jonathan Roberts 1
Panagiotis Ritsos 1
Claus Madsen 1
Michael Zollhöfer 1
Ivor Pridden 1
Liz Sonenberg 1
Massimo Zancanaro 1
Maria Melo 1
Christian Pere 1
Irving Finkle 1
Judith Aston 1
Luís Magalhães 1
João Moura 1
Fabio Remondino 1
David Koller 1
Zhijun Sun 1
Marco De Gemmis 1
Cataldo Musto 1
Sven Schutte 1
Andreas Vlachopoulos 1
Blanca Acuña 1
Horst Bischof 1
Panayiotis Charalambous 1
Bianca Falcidieno 1
Qingquan Li 1
Ilan Shimshoni 1
Jennifer Gutierrez 1
Chandra Kambhamettu 1
D Drinkwater 1
Qiong Li 1
Doron Goldfarb 1
Gerd Reis 1
Didier Stricker 1
Werner Purgathofer 1
Mauricio Hincapié 1
Stefan Rennick Egglestone 1
Jean Odobez 1
Edgar Roman-Rangel 1
Mariam Samaan 1
Giovanni Puglisi 1
Dalibor Mitrović 1
Fabiana Zeppa 1
David Smith 1
Gulcan Can 1
Philip Sapirstein 1
Eric Psota 1
Marc Deseilligny 1
Donato Malerba 1
Fabio Gadducci 1
Christine Chevrier 1
Germana Barone 1
Claudia Barberis 1
Eliana Siotto 1
Fabrice Evrard 1
Alain Bonardi 1
Nazrita Ibrahim 1
Kyriakos Herakleous 1
Fumio Okura 1
Giorgio Trumpy 1
Immanuel Normann 1
Alejandro León 1
M Luzón 1
Stuart Dunn 1
Jaime Kaminski 1
Elwira Holowko 1
Jeffrey Trevino 1
James Gain 1
Fabian Bohnert 1
Changle Zhou 1
Andrea Adami 1
Nuno Correia 1
Sotiris Manitsaris 1
Frédéric Bevilacqua 1
Brett Ridel 1
M Gaiani 1
Sarah Kenderdine 1
Emmanuel Durand 1
Frédéric Mérienne 1
Loic Espinasse 1
Bin Ma 1
Panayiotis Roussopoulos 1
Yogesh Garg 1
Thomas Hurtut 1
James Clarke 1
Cinzia Perlingieri 1
Ismail Altingövde 1
Fedelucio Narducci 1
Atte Timonen 1
Luc Long 1
Fabrizio Falchi 1
George Leifman 1
Rohith Mv 1
Andrew Day 1
Kris Naessens 1
Daniele Mori 1
Johannes Kohler 1
Antonio Castañeda 1
Jin Liu 1
Vanessa Lardinois 1
Greg Humphreys 1
Giovanni Semeraro 1
Stephan Schreiber 1
Klaus Hinzen 1
Christos Doumas 1
Jordi Moyes 1
Veronica Sundstedt 1
Silvia Biasotti 1
Mo Shan 1
Bilal Hijazi 1
Emmanuelle Seguin 1
Debra Norris 1
Stephanie Schnorr 1
Suzanne De Jong-Kole 1
Corey Toler-Franklin 1
Christian Diaz 1
Joaquin Mora 1
Daniel Gatica-Perez 1
Gregory Knight 1
Marco Mason 1
P Nieri 1
G Cox 1
Filippo Stanco 1
Santanu Chaudhury 1
Hiranmay Ghosh 1
David Bamman 1
Martin Kampel 1
Karl Lampe 1
Douglas Oard 1
Nazlena Mohamad Ali 1
Irene Katsouri 1
Stavroula Bampatzia 1
David Arnold 1
Marc Stamminger 1
Chiara Stefani 1
Julie Lombardo 1
Philippe Véron 1
Ariel Gorfinkel 1
Xiaojun Ding 1
Athina Kritsotaki 1
A Ricardo 1
R Castro 1
R Carvalho 1
Fabien Moutarde 1
Patrick Reuter 1
Paul Matthews 1
Patrick Reuter 1
Guillaume Riviere 1
Stefania Serafin 1
Barbara Thuswaldner 1
Alexandrino Gonçalves 1
Yann Gousseau 1
Victor Obonyo 1
Ismet Yalniz 1
Peter Fornaro 1
Alessandro Foni 1
Pasquale Lops 1
Guido Ranzuglia 1
Pere Brunet 1
Jeremy Hutchings 1
Michela Spagnuolo 1
Bertrand Chemisky 1
Giuseppe Amato 1
Hadas Zohar 1
Yingqing Xu 1
Tanguy Coenen 1
Lien Mostmans 1
Tobias Nöll 1
Daniel O’donnell 1
Holly Rushmeier 1
Stefan Maierhofer 1
Benedict Brown 1
Davide Angheleddu 1
David Buglio 1
Diego Jimenez-Badillo 1
Carmen Diaz-Marin 1
Gabriele Fangi 1
Fabio Fumarola 1
Bilel Elayeb 1
Yahya Slimani 1
Anupama Mallik 1
Hagen Hirschmann 1
F Soler 1
Engtat Khoo 1
Holly Rushmeier 1
John Ffrench 1
Frédéric Labrosse 1
Joseph Mearman 1
Serdar Aybek 1
Jerzy Wojsz 1
Tonya Nelson 1
Bruce Merry 1
Oliviero Stock 1
Katerina Boutsika 1
Daniel Aliaga 1
Tarquinio Mota 1
Leith Chan 1
Michael Makridis 1
Ashraf Hussein 1
Robert Kalasek 1
Qixing Huang 1
Sven Havemann 1
Gualtiero Volpe 1
Farida Chériet 1
Bernard Frischer 1
Florian Muller 1
George Papagiannakis 1
Nadia Magnenat-Thalmann 1
Zheng Lu 1
Antoni Chica 1
Samuel Schulter 1
Mohamed Djibril 1
Diego Gutierrez 1
Stephania Himona 1
Djamel Merad 1
Jean Boï 1
Ido Dagan 1
Jane Tarakhovsky 1
Max Arends 1
Joost Van Leusen 1
Ying Yang 1
David Dobkin 1
Gabriele Guidi 1
Amy Friedlander 1
Nasseh Tabrizi 1
I Cacciari 1
Antonio Felle 1
Giovanni Cignoni 1
Miguel Sanchez-Lopez 1
Ibrahim Bounhas 1
Jacques Roger 1
George Roussos 1
Wenching Liao 1
Mengchieh Yu 1
Sebastian Zambanini 1
Genfang Chen 1
Dolores Iorizzo 1
Sven Helmer 1
Juan Torres 1
Maciej Karaszewski 1
Min Kim 1
Irma Passeri 1
Rossana Damiano 1
B Dreyer 1
Giancarlo Amati 1
Roland Ruiters 1
Reinhard Klein 1
Shahar Kats 1
Julia Sheidin 1
Minjun Jiang 1
Jeffrey Shaw 1
Stephanie Mahut 1
Mark Mudge 1
Mark Stevenson 1
Hilke Thur 1
Antonio Camurri 1
Lorenzo Gonzo 1
Michael Ashley 1
Christian Reinbacher 1
Jonathan Smith 1
Andrea Cerri 1
Julien Seinturier 1
Gowri Somanath 1
Robert Laycock 1
Charlotte Hug 1
Chihhong Huang 1
Camilo Mesias 1
Alonzo Addison 1
Boriana Koleva 1
Maria Roussou 1
Sofia Pescarin 1
Michelangelo Ceci 1
Tommi Horttana 1
Paolo Mazzoleni 1
Jetmir Xhembulla 1
Giovanni Malnati 1
Etienne De La Vaissiere 1
Theano Moussouri 1
Christian Hörr 1
Elisabeth Lindinger 1
Chunko Hsieh 1
Khurshid Ahmad 1
Jerome Barthelemy 1
Roeland Ordelman 1
Noor Mohd Yatim 1
Aimilia Tzanavari 1
Richard Brownlow 1
Erica Calogero 1
Ryohei Nakatsu 1
Adrian Cheok 1
Craig Sapp 1
Helen Miles 1
Ben Edwards 1
Katharina Moller 1
Barbara Pavlek 1
Chawee Busayarat 1
Nadav Kashtan 1
Enzhi Ni 1
Stefano Valtolina 1
Nicolas Mellado 1
Patrick Callet 1
Mark Greco 1
Annamaria D'ursi 1
Mihalis Exarhos 1
Paul Clough 1
Qing Sun 1
Hisham El-Shishiny 1
Amalia De Götzen 1

Affiliation Paper Counts
University of Padua 1
Frederick University Cyprus 1
Universite Victor Segalen Bordeaux 2 1
Austrian Academy of Sciences 1
University of Ioannina 1
University of Applied Sciences of Karlsruhe 1
Universiti Tenaga Nasional 1
Xi'an University of Finance and Economics 1
The University of Hong Kong 1
Spanish National Research Council 1
University of Leipzig 1
University of Zagreb 1
Free University of Bozen-Bolzano 1
Technical University of Darmstadt 1
King's College London 1
Ionian University 1
City University of Hong Kong 1
University of Waterloo 1
University of Massachusetts Amherst 1
Imperial College London 1
Ain Shams University 1
Xi'an Jiaotong University 1
Celal Bayar University 1
Polytechnic School of Montreal 1
Foundation for Research and Technology-Hellas 1
Monash University 1
University of Maryland 1
University of Bristol 1
University of Surrey 1
Universite Paris 1 Pantheon-Sorbonne 1
Massachusetts Institute of Technology 1
Ecole Centrale Paris 1
University of Lethbridge 1
Catholic University of Leuven 1
EHESS Ecole des Hautes Etudes en Sciences Sociales 1
University of Thessaly 1
University of Bologna 1
University of New South Wales 1
Polytechnic Institute of Leiria 1
Universite Paris Descartes 1
University of Milan 1
University of Bath 1
IRIT Institut de Recherche Informatique de Toulouse 1
Ecole des Mines de Paris 1
Scuola Normale of Pisa 1
University of Cambridge 1
Korea Advanced Institute of Science & Technology 1
University of Cagliari 1
Tata Consultancy Services India 1
Hangzhou Normal University 1
Cultural Heritage Imaging, California 1
Universite de Bordeaux 1
E2v 1
University of Nicosia 1
Royal College of Art 1
Shenzhen University 1
Universiti Kebangsaan Malaysia 2
Istituto Di Fisica Applicata Nello Carrara 2
The British Museum 2
Lawrence Technological University 2
VRVis Research Center 2
Chemnitz University of Technology 2
Purdue University 2
University of Oslo 2
University of Dublin, Trinity College 2
National Taipei University of Technology 2
Stanford University 2
University of Tras-os-Montes and Alto Douro 2
East Carolina University 2
Universidad de Zaragoza 2
Mohammed V University in Rabat 2
University of the West of England 2
Maulana Azad National Institute of Technology 2
The University of Warwick 2
Manchester Metropolitan University 2
Tufts University 2
Beijing Normal University 2
Politecnico di Milano 2
St. Polten University of Applied Sciences 2
University of Nebraska - Lincoln 2
University of Turku School of Cultural Production and Landscape Studies 2
TELECOM ParisTech 2
University of Queensland 2
University of Gottingen 2
Indian Institute of Technology, Delhi 2
Universitat Pompeu Fabra 2
University of Seville 2
European Commission Joint Research Centre, Ispra 2
University of Manouba 2
Zoologisches Forschungsmuseum Alexander Koenig 2
Centro de Quimica fina e Biotecnologia 2
Fondazione Bruno Kessler 2
Faculty of Social Sciences and Humanities, Universidade Nova de Lisboa 2
University of Cape Town 3
University of Erlangen-Nuremberg 3
University of Sheffield 3
University of Brighton 3
University of Catania 3
University of Turin 3
Institut de Recherche et Coordination Acoustique Musique 3
Peking University 3
University of Twente 3
University of Virginia 3
Aalborg University 3
Technion - Israel Institute of Technology 3
University of Cologne 3
Nara Institute of Science and Technology 3
University of California, Berkeley 3
University of Melbourne 3
Vrije Universiteit Brussel 3
Swiss Federal Institute of Technology, Lausanne 3
Aberystwyth University 3
Marche Polytechnic University 3
Miami University Oxford 3
Cyprus University of Technology 3
Arts et Metiers ParisTech 3
Humboldt University of Berlin 4
Bar-Ilan University 4
Warsaw University of Technology 4
University of Peloponnese 4
National Taiwan University 4
University of Bonn 4
Universitat Politecnica de Catalunya 4
Universidad Politecnica de Valencia 4
Polytechnic Institute of Turin 4
Bilkent University 4
University of Nottingham 4
Xiamen University 4
Universidad de Granada 4
University of Athens 4
New University of Lisbon 4
Institute of Computer Science Crete 4
University of Cyprus 4
German Research Center for Artificial Intelligence (DFKI) 4
Universidad de Medellin 4
National Technical University of Athens 5
University of Geneva 5
University of Delaware 5
University of Pisa 5
Microsoft Research Asia 5
Aix Marseille Universite 5
University of East Anglia 6
Birkbeck University of London 6
University of Basel 6
Bangor University 6
University of Haifa 7
National University of Singapore 7
Aalto University 7
CNRS Centre National de la Recherche Scientifique 8
Italian National Research Council 8
Yale University 9
Princeton University 10
Graz University of Technology 10
University of Bari 10
University College London 11
University of Genoa 13
Vienna University of Technology 16
Istituto di Scienza e Tecnologie dell'Informazione A. Faedo 22
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