Development of a System to Assist Automatic Translation of Hand-Drawn Maps into Tactile Graphics and Its Usability Evaluation

Tactile graphics are images that use raised surfaces so that a visually impaired person can feel them. Tactile maps are used by blind and partially sighted people when navigating around an environment, and they are also used prior to a visit for orientation purposes. Since the ability to read tactile graphics deeply depends on individuals, providing tactile graphics individually is needed. This implies that producing tactile graphics should be as simple as possible. Based on this background, we are developing a system for automating production of tactile maps from hand-drawn figures. In this paper, we first present a pattern recognition method for hand-drawn maps. The usability of our system is then evaluated by comparing it with the two different methods to produce tactile graphics

Translating Scientific Content into Accessible Formats with Visually Impaired Learners: Recommendations and a Decision Aid Based on Haptic Rules of Perception

Students with visual impairments (VI) miss out on science because of inaccessible visual graphics (such as pictures and diagrams) of the phenomena that are the focus of curricula. My project examines how efforts to translate these into non-visual representations, such as raised line graphics, tend to be less effective than expected because they are perceived using “rules” of haptic perception by VI learners but developed using “rules”' of visual perception by sighted designers. In response, I introduce my recommendations, in the form of a decision aid, informed by a series of interlinked concatenated studies consisting of user testing, workshops, and co-design sessions composed of multi-disciplinary teams that included VI educators, learners, inclusive designers, musicians, and domain experts from engineering and the cognitive neuroscience

Ontologies and representation spaces for sketch map interpretation

In this paper, we present a systematic approach to sketch map interpretation. The method decomposes the elements of a sketch map into a hierarchy of categories, from the material sketch map level to the non-material representational sketch map level, and then interprets the sketch map using the five formal representation spaces that we develop. These spaces (set, graph, metric and Euclidean) provide a tiered formal representation based on standard mathematical structures. We take the view that a sketch map bears information about the physical world and systematises this using extensions of existing formal ontologies. The motivation for this work is the partially automatic extraction and integration of information from sketch maps. We propose a set of ontologies and methods as a first step in the direction of a formalisation of partially automatic extraction and integration of sketch map content. We also see this work as a contribution to spatial cognition, where researchers externalise spatial knowledge using sketch mapping. The paper concludes by working through an example that demonstrates the sketch map interpretation at different levels using the underlying method

Tabletop tangible maps and diagrams for visually impaired users

En dépit de leur omniprésence et de leur rôle essentiel dans nos vies professionnelles et personnelles, les représentations graphiques, qu'elles soient numériques ou sur papier, ne sont pas accessibles aux personnes déficientes visuelles car elles ne fournissent pas d'informations tactiles. Par ailleurs, les inégalités d'accès à ces représentations ne cessent de s'accroître ; grâce au développement de représentations graphiques dynamiques et disponibles en ligne, les personnes voyantes peuvent non seulement accéder à de grandes quantités de données, mais aussi interagir avec ces données par le biais de fonctionnalités avancées (changement d'échelle, sélection des données à afficher, etc.). En revanche, pour les personnes déficientes visuelles, les techniques actuellement utilisées pour rendre accessibles les cartes et les diagrammes nécessitent l'intervention de spécialistes et ne permettent pas la création de représentations interactives. Cependant, les récentes avancées dans le domaine de l'adaptation automatique de contenus laissent entrevoir, dans les prochaines années, une augmentation de la quantité de contenus adaptés. Cette augmentation doit aller de pair avec le développement de dispositifs utilisables et abordables en mesure de supporter l'affichage de représentations interactives et rapidement modifiables, tout en étant accessibles aux personnes déficientes visuelles. Certains prototypes de recherche s'appuient sur une représentation numérique seulement : ils peuvent être instantanément modifiés mais ne fournissent que très peu de retour tactile, ce qui rend leur exploration complexe d'un point de vue cognitif et impose de fortes contraintes sur le contenu. D'autres prototypes s'appuient sur une représentation numérique et physique : bien qu'ils puissent être explorés tactilement, ce qui est un réel avantage, ils nécessitent un support tactile qui empêche toute modification rapide. Quant aux dispositifs similaires à des tablettes Braille, mais avec des milliers de picots, leur coût est prohibitif. L'objectif de cette thèse est de pallier les limitations de ces approches en étudiant comment développer des cartes et diagrammes interactifs physiques, modifiables et abordables. Pour cela, nous nous appuyons sur un type d'interface qui a rarement été étudié pour des utilisateurs déficients visuels : les interfaces tangibles, et plus particulièrement les interfaces tangibles sur table. Dans ces interfaces, des objets physiques représentent des informations numériques et peuvent être manipulés par l'utilisateur pour interagir avec le système, ou par le système lui-même pour refléter un changement du modèle numérique - on parle alors d'interfaces tangibles sur tables animées, ou actuated. Grâce à la conception, au développement et à l'évaluation de trois interfaces tangibles sur table (les Tangible Reels, la Tangible Box et BotMap), nous proposons un ensemble de solutions techniques répondant aux spécificités des interfaces tangibles pour des personnes déficientes visuelles, ainsi que de nouvelles techniques d'interaction non-visuelles, notamment pour la reconstruction d'une carte ou d'un diagramme et l'exploration de cartes de type " Pan & Zoom ". D'un point de vue théorique, nous proposons aussi une nouvelle classification pour les dispositifs interactifs accessibles.Despite their omnipresence and essential role in our everyday lives, online and printed graphical representations are inaccessible to visually impaired people because they cannot be explored using the sense of touch. The gap between sighted and visually impaired people's access to graphical representations is constantly growing due to the increasing development and availability of online and dynamic representations that not only give sighted people the opportunity to access large amounts of data, but also to interact with them using advanced functionalities such as panning, zooming and filtering. In contrast, the techniques currently used to make maps and diagrams accessible to visually impaired people require the intervention of tactile graphics specialists and result in non-interactive tactile representations. However, based on recent advances in the automatic production of content, we can expect in the coming years a growth in the availability of adapted content, which must go hand-in-hand with the development of affordable and usable devices. In particular, these devices should make full use of visually impaired users' perceptual capacities and support the display of interactive and updatable representations. A number of research prototypes have already been developed. Some rely on digital representation only, and although they have the great advantage of being instantly updatable, they provide very limited tactile feedback, which makes their exploration cognitively demanding and imposes heavy restrictions on content. On the other hand, most prototypes that rely on digital and physical representations allow for a two-handed exploration that is both natural and efficient at retrieving and encoding spatial information, but they are physically limited by the use of a tactile overlay, making them impossible to update. Other alternatives are either extremely expensive (e.g. braille tablets) or offer a slow and limited way to update the representation (e.g. maps that are 3D-printed based on users' inputs). In this thesis, we propose to bridge the gap between these two approaches by investigating how to develop physical interactive maps and diagrams that support two-handed exploration, while at the same time being updatable and affordable. To do so, we build on previous research on Tangible User Interfaces (TUI) and particularly on (actuated) tabletop TUIs, two fields of research that have surprisingly received very little interest concerning visually impaired users. Based on the design, implementation and evaluation of three tabletop TUIs (the Tangible Reels, the Tangible Box and BotMap), we propose innovative non-visual interaction techniques and technical solutions that will hopefully serve as a basis for the design of future TUIs for visually impaired users, and encourage their development and use. We investigate how tangible maps and diagrams can support various tasks, ranging from the (re)construction of diagrams to the exploration of maps by panning and zooming. From a theoretical perspective we contribute to the research on accessible graphical representations by highlighting how research on maps can feed research on diagrams and vice-versa. We also propose a classification and comparison of existing prototypes to deliver a structured overview of current research

Designing multi-sensory displays for abstract data

The rapid increase in available information has lead to many attempts to automatically locate patterns in large, abstract, multi-attributed information spaces. These techniques are often called data mining and have met with varying degrees of success. An alternative approach to automatic pattern detection is to keep the user in the exploration loop by developing displays for perceptual data mining. This approach allows a domain expert to search the data for useful relationships and can be effective when automated rules are hard to define. However, designing models of the abstract data and defining appropriate displays are critical tasks in building a useful system. Designing displays of abstract data is especially difficult when multi-sensory interaction is considered. New technology, such as Virtual Environments, enables such multi-sensory interaction. For example, interfaces can be designed that immerse the user in a 3D space and provide visual, auditory and haptic (tactile) feedback. It has been a goal of Virtual Environments to use multi-sensory interaction in an attempt to increase the human-to-computer bandwidth. This approach may assist the user to understand large information spaces and find patterns in them. However, while the motivation is simple enough, actually designing appropriate mappings between the abstract information and the human sensory channels is quite difficult. Designing intuitive multi-sensory displays of abstract data is complex and needs to carefully consider human perceptual capabilities, yet we interact with the real world everyday in a multi-sensory way. Metaphors can describe mappings between the natural world and an abstract information space. This thesis develops a division of the multi-sensory design space called the MS-Taxonomy. The MS-Taxonomy provides a concept map of the design space based on temporal, spatial and direct metaphors. The detailed concepts within the taxonomy allow for discussion of low level design issues. Furthermore the concepts abstract to higher levels, allowing general design issues to be compared and discussed across the different senses. The MS-Taxonomy provides a categorisation of multi-sensory design options. However, to design effective multi-sensory displays requires more than a thorough understanding of design options. It is also useful to have guidelines to follow, and a process to describe the design steps. This thesis uses the structure of the MS-Taxonomy to develop the MS-Guidelines and the MS-Process. The MS-Guidelines capture design recommendations and the problems associated with different design choices. The MS-Process integrates the MS-Guidelines into a methodology for developing and evaluating multi-sensory displays. A detailed case study is used to validate the MS-Taxonomy, the MS-Guidelines and the MS-Process. The case study explores the design of multi-sensory displays within a domain where users wish to explore abstract data for patterns. This area is called Technical Analysis and involves the interpretation of patterns in stock market data. Following the MS-Process and using the MS-Guidelines some new multi-sensory displays are designed for pattern detection in stock market data. The outcome from the case study includes some novel haptic-visual and auditory-visual designs that are prototyped and evaluated

Deep learning for object detection in robotic grasping contexts

Dans la dernière décennie, les approches basées sur les réseaux de neurones convolutionnels sont devenus les standards pour la plupart des tâches en vision numérique. Alors qu'une grande partie des méthodes classiques de vision étaient basées sur des règles et algorithmes, les réseaux de neurones sont optimisés directement à partir de données d'entraînement qui sont étiquetées pour la tâche voulue. En pratique, il peut être difficile d'obtenir une quantité su sante de données d'entraînement ou d'interpréter les prédictions faites par les réseaux. Également, le processus d'entraînement doit être recommencé pour chaque nouvelle tâche ou ensemble d'objets. Au final, bien que très performantes, les solutions basées sur des réseaux de neurones peuvent être difficiles à mettre en place. Dans cette thèse, nous proposons des stratégies visant à contourner ou solutionner en partie ces limitations en contexte de détection d'instances d'objets. Premièrement, nous proposons d'utiliser une approche en cascade consistant à utiliser un réseau de neurone comme pré-filtrage d'une méthode standard de "template matching". Cette façon de faire nous permet d'améliorer les performances de la méthode de "template matching" tout en gardant son interprétabilité. Deuxièmement, nous proposons une autre approche en cascade. Dans ce cas, nous proposons d'utiliser un réseau faiblement supervisé pour générer des images de probabilité afin d'inférer la position de chaque objet. Cela permet de simplifier le processus d'entraînement et diminuer le nombre d'images d'entraînement nécessaires pour obtenir de bonnes performances. Finalement, nous proposons une architecture de réseau de neurones ainsi qu'une procédure d'entraînement permettant de généraliser un détecteur d'objets à des objets qui ne sont pas vus par le réseau lors de l'entraînement. Notre approche supprime donc la nécessité de réentraîner le réseau de neurones pour chaque nouvel objet.In the last decade, deep convolutional neural networks became a standard for computer vision applications. As opposed to classical methods which are based on rules and hand-designed features, neural networks are optimized and learned directly from a set of labeled training data specific for a given task. In practice, both obtaining sufficient labeled training data and interpreting network outputs can be problematic. Additionnally, a neural network has to be retrained for new tasks or new sets of objects. Overall, while they perform really well, deployment of deep neural network approaches can be challenging. In this thesis, we propose strategies aiming at solving or getting around these limitations for object detection. First, we propose a cascade approach in which a neural network is used as a prefilter to a template matching approach, allowing an increased performance while keeping the interpretability of the matching method. Secondly, we propose another cascade approach in which a weakly-supervised network generates object-specific heatmaps that can be used to infer their position in an image. This approach simplifies the training process and decreases the number of required training images to get state-of-the-art performances. Finally, we propose a neural network architecture and a training procedure allowing detection of objects that were not seen during training, thus removing the need to retrain networks for new objects

Extending Discourse Analysis in Archaeology: A Multimodal Approach

Archaeology is a highly visual discipline, reliant on observation as well as description, and consequently makes extensive use of diagrams, maps, plans, illustrations and photography as well as textual narratives in communicating its interpretations of past material culture. If discourse analysis is to shed light on the construction of archaeological knowledge it therefore should seek to incorporate the visual alongside the textual, but at present discussion of the two modes are largely independent of each other with an emphasis on the text. A case study examines the interrelationships and interdependencies that exist between text and illustrations in archaeological grey literature, and argues that a multimodal approach to knowledge creation is called for which better reflects the different modes and media used in archaeology