H. F. Pinto, Carlos de Salles Soares Neto, S. Colcher, R. Azevedo
{"title":"The Fábulas Model for Authoring Web-based Children's eBooks","authors":"H. F. Pinto, Carlos de Salles Soares Neto, S. Colcher, R. Azevedo","doi":"10.1145/3103010.3103016","DOIUrl":"https://doi.org/10.1145/3103010.3103016","url":null,"abstract":"Nowadays, tablets and smartphones are commonly used by children for both entertainment and education purposes. In special, interactive multimedia eBooks running on those devices allow a richer experience when compared to traditional text-only books, being potentially more engaging and entertaining to readers. However, to explore the most exciting features in these environments, authors are currently left alone in the sense that there is no high level (less technical) support, and these features are usually accessible only through programming or some other technical skill. In this work, we aim at extracting the main features on enhanced children's eBooks and propose a model, named Fábulas - the Portuguese word for fables -that allows authors to create interactive multimedia children's eBooks declaratively. The model was conceived by taking, as a starting point, a systematic analysis of the common concepts, with the focus on identifying and categorizing recurring characteristics and pointing out functional and non-functional requirements that establish a strong orientation towards the set of desirable abstractions of an underlying model. Moreover, the paper presents a case study for the implementation of Fábulas on the Web, and discusses the authoring of a complete interactive story over it.","PeriodicalId":200469,"journal":{"name":"Proceedings of the 2017 ACM Symposium on Document Engineering","volume":"354 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122792887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sketched Visual Narratives for Image and Video Search","authors":"J. Collomosse","doi":"10.1145/3103010.3103024","DOIUrl":"https://doi.org/10.1145/3103010.3103024","url":null,"abstract":"The internet is transforming into a visual medium; over 80% of the internet is forecast to be visual content by 2018, and most of this content will be consumed on mobile devices featuring a touch-screen as their primary interface. Gestural interaction, such as sketch, presents an intuitive way to interact with these devices. Imagine a Google image search in which you specify your query by sketching the desired image with your finger, rather than (or in addition to) describing it with text words. Sketch offers an orthogonal perspective on visual search - enabling concise specification of appearance (via sketch) in addition to semantics (via text). In this talk, John Collomosse will present a summary of his group's work on the use of free-hand sketches for the visual search and manipulation of images and video. He will begin by describing a scalable system for sketch based search of multi-million image databases, based upon their Gradient Field HOG (GF-HOG) descriptor. He will then describe how deep learning can be used to enhance performance of the retrieval. Imagine a product catalogue in which you sketched, say an engineering part, rather than using a text or serial numbers to find it? John will then describe how scalable search of video can be similarly achieved, through the depiction of sketched visual narratives that depict not only objects but also their motion (dynamics) as a constraint to find relevant video clips. The work presented in this talk has been supported by the EPSRC and AHRC between 2012-2016.","PeriodicalId":200469,"journal":{"name":"Proceedings of the 2017 ACM Symposium on Document Engineering","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124947316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alexandra Bonnici, Stefania Cristina, K. Camilleri
{"title":"Preparation of Music Scores to Enable Hands-free Page Turning Based on Eye-gaze Tracking","authors":"Alexandra Bonnici, Stefania Cristina, K. Camilleri","doi":"10.1145/3103010.3103012","DOIUrl":"https://doi.org/10.1145/3103010.3103012","url":null,"abstract":"Digital copies of musical scores may be saved on tablet devices, compressing volumes of scores into a single portable device. Tablet screens are however typically smaller than printed sheet music such that the score needs to be resized for readability. This necessitates additional page turning which is made more complex when repeat instructions are used since these give rise to forward and backward page turns of the music. In this paper, we tackle this problem by first performing image analysis of the score in order to identify repeat instructions and hence flatten the score. Thus, the music player is presented the score as it should be played. We then propose the use of eye-gaze tracking to provide a hands-free page turning mechanism. Thus, the player remains in full control of when the page turn occurs. Through a preliminary study, we found that our proposed score flattening and eye-gaze page turning reduced the time spent navigating the page turns by 47% in comparison to available music score reading tools.","PeriodicalId":200469,"journal":{"name":"Proceedings of the 2017 ACM Symposium on Document Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128756324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Small-Term Distribution for Disk-Based Search","authors":"Andrew Kane, Frank Wm. Tompa","doi":"10.1145/3103010.3103022","DOIUrl":"https://doi.org/10.1145/3103010.3103022","url":null,"abstract":"A disk-based search system distributes a large index across multiple disks on one or more machines, where documents are typically assigned to disks at random in order to achieve load balancing. However, random distribution degrades clustering, which is required for efficient index compression. Using the GOV2 dataset, we demonstrate the effect of various ordering techniques on index compression, and then quantify the effect of various document distribution approaches on compression and load balancing. We explore runtime performance by simulating a disk-based search system for a scaled-out 10xGOV2 index over ten disks using two standard approaches, document and term distribution, as well as a hybrid approach: small-term distribution. We find that small-term distribution has the best performance, especially in the presence of list caching, and argue that this rarely discussed distribution approach can improve disk-based search performance for many real-world installations.","PeriodicalId":200469,"journal":{"name":"Proceedings of the 2017 ACM Symposium on Document Engineering","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129970751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Learning before Learning: Reversing Validation and Training","authors":"S. Simske, M. Vans","doi":"10.1145/3103010.3121044","DOIUrl":"https://doi.org/10.1145/3103010.3121044","url":null,"abstract":"In the world of ground truthing--that is, the collection of highly valuable labeled training and validation data-there is a tendency to follow the path of first training on a set of data, then validating the data, and then testing the data. However, in many cases the labeled training data is of non-uniform quality, and thus of non-uniform value for assessing the accuracy and other performance indicators for analytics algorithms, systems and processes. This means that one or more of the so-labeled classes is likely a mixture of two or more clusters or sub-classes. These data may inhibit our ability to assess the classifier to use for deployment. We argue that one must learn about the labeled data before the labeled data can be used for downstream machine learning; that is, we reverse the validation and training steps in building the classifier. This \"learning before learning\" is assessed using a CNN corpus (cnn.com) which was hand-labeled as comprising 12 classes. We show how the suspect classes are identified using the initial validation, and how training after validation occurs. We then apply this process to the CNN corpus and show that it consists of 9 high-quality classes and three mixed-quality classes. The effects of this validation-training approach is then shown and discussed.","PeriodicalId":200469,"journal":{"name":"Proceedings of the 2017 ACM Symposium on Document Engineering","volume":"94 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129983355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Improving Version-Aware Word Documents","authors":"Alexandre Azevedo Filho, E. Munson, C. Thao","doi":"10.1145/3103010.3121027","DOIUrl":"https://doi.org/10.1145/3103010.3121027","url":null,"abstract":"Coakley et al. described how they developed Version Aware Word Documents, which is an enhanced document representation that includes a detailed version history that is self-contained and portable. However, they were not able to adopt the unique-ID-based techniques that have been shown to support efficient merging and differencing algorithms. This application note describes how it is possible to adapt existing features of MS Word's OOXML representation to provide a system of unique element IDs suitable for those algorithms. This requires taking over Word's Revision Save ID (RSID) system and also defining procedures for specifying ID values for elements that do not support the RSID mechanism. Important limitations remain but appear surmountable.","PeriodicalId":200469,"journal":{"name":"Proceedings of the 2017 ACM Symposium on Document Engineering","volume":"89 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126314040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Loutfouz Zaman, W. Stuerzlinger, Christian Neugebauer
{"title":"MACE: A New Interface for Comparing and Editing of Multiple Alternative Documents for Generative Design","authors":"Loutfouz Zaman, W. Stuerzlinger, Christian Neugebauer","doi":"10.1145/3103010.3103013","DOIUrl":"https://doi.org/10.1145/3103010.3103013","url":null,"abstract":"We present a new interface for interactive comparisons of more than two alternative documents in the context of a generative design system that uses generative data-flow networks defined via directed acyclic graphs. To better show differences between such networks, we emphasize added, deleted, (un)changed nodes and edges. We emphasize differences in the output as well as parameters using highlighting and enable post-hoc merging of the state of a parameter across a selected set of alternatives. To minimize visual clutter, we introduce new difference visualizations for selected nodes and alternatives using additive and subtractive encodings, which improve readability and keep visual clutter low. We analyzed similarities in networks from a set of alternative designs produced by architecture students and found that the number of similarities outweighs the differences, which motivates use of subtractive encoding. We ran a user study to evaluate the two main proposed difference visualization encodings and found that they are equally effective.","PeriodicalId":200469,"journal":{"name":"Proceedings of the 2017 ACM Symposium on Document Engineering","volume":"170 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130617799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Uscamayta, Bruna C. R. Cunha, D. Martins, M. G. Pimentel
{"title":"Opportunistic Collaborative Mobile-Based Multimedia Authoring Based on the Capture of Live Experiences","authors":"A. Uscamayta, Bruna C. R. Cunha, D. Martins, M. G. Pimentel","doi":"10.1145/3103010.3121047","DOIUrl":"https://doi.org/10.1145/3103010.3121047","url":null,"abstract":"Despite recent results allowing collaborative video capture using mobile devices, there is a gap in promoting collaborative capture of media other than video. In this paper we report our collaborative model supporting amateur and opportunistic collaborative recording of multiple media using mobile devices. We present a case study carried out in the educational domain. We include a motivating scenario and related requirements, our proposed architecture and associated proof-of-concept prototype for supporting mobile amateur collaborative recording.","PeriodicalId":200469,"journal":{"name":"Proceedings of the 2017 ACM Symposium on Document Engineering","volume":"51 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127997375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Session details: Keynote I","authors":"K. Camilleri","doi":"10.1145/3248705","DOIUrl":"https://doi.org/10.1145/3248705","url":null,"abstract":"","PeriodicalId":200469,"journal":{"name":"Proceedings of the 2017 ACM Symposium on Document Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126442299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fast Binarisation with Chebyshev Inequality","authors":"Ka‐Hou Chan, S. Im, Wei Ke","doi":"10.1145/3103010.3121033","DOIUrl":"https://doi.org/10.1145/3103010.3121033","url":null,"abstract":"In order to enhance the binarization result of degraded document images with smudged and bleed-through background, we present a fast binarization technique that applies the Chebyshev theory in the image preprocessing. We introduce the Chebyshev filter which uses the Chebyshev inequality in the segmentation of objects and background. Our result shows that the Chebyshev filter is not only effective, but also simple, robust and easy to implement. Because of its simplicity, our method is sufficiently efficient to process live image sequences in real-time. We have implemented and compared with the Document Image Binarization Contest datasets (H-DIBCO 2014) for testing and evaluation. The experimental outcomes have demonstrated that this method achieved good result in this literature.","PeriodicalId":200469,"journal":{"name":"Proceedings of the 2017 ACM Symposium on Document Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130170514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}