Outdoor Augmented Reality: State of the Art and Issues

International audienceThe goal of an outdoor augmented reality system is to allow the human operator to move freely without restraint in its environment, to view and interact in real time with geo-referenced data via mobile wireless devices. This requires proposing new techniques for 3D localization, visualization and 3D interaction, adapted to working conditions in outdoor environment (brightness variation, features of displays used, etc.). This paper surveys recent advances in outdoor augmented reality. It resumes a large retrospective of the work carried out in this field, especially on methodological aspects (localization methods, generation of 3D models, visualization and interaction approaches), technological aspects (sensors, visualization devices and architecture software) and industrial aspects

SandCanvas: A Multi-touch Art Medium Inspired by Sand Animation

10.1145/1978942.1979133Conference on Human Factors in Computing Systems - Proceedings1283-129

Contex-aware gestures for mixed-initiative text editings UIs

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Interacting with computers following peer review. The version of record is available online at: http://dx.doi.org/10.1093/iwc/iwu019[EN] This work is focused on enhancing highly interactive text-editing applications with gestures. Concretely, we study Computer Assisted Transcription of Text Images (CATTI), a handwriting transcription system that follows a corrective feedback paradigm, where both the user and the system collaborate efficiently to produce a high-quality text transcription. CATTI-like applications demand fast and accurate gesture recognition, for which we observed that current gesture recognizers are not adequate enough. In response to this need we developed MinGestures, a parametric context-aware gesture recognizer. Our contributions include a number of stroke features for disambiguating copy-mark gestures from handwritten text, plus the integration of these gestures in a CATTI application. It becomes finally possible to create highly interactive stroke-based text-editing interfaces, without worrying to verify the user intent on-screen. We performed a formal evaluation with 22 e-pen users and 32 mouse users using a gesture vocabulary of 10 symbols. MinGestures achieved an outstanding accuracy (<1% error rate) with very high performance (<1 ms of recognition time). We then integrated MinGestures in a CATTI prototype and tested the performance of the interactive handwriting system when it is driven by gestures. Our results show that using gestures in interactive handwriting applications is both advantageous and convenient when gestures are simple but context-aware. Taken together, this work suggests that text-editing interfaces not only can be easily augmented with simple gestures, but also may substantially improve user productivity.This work has been supported by the European Commission through the 7th Framework Program (tranScriptorium: FP7- ICT-2011-9, project 600707 and CasMaCat: FP7-ICT-2011-7, project 287576). It has also been supported by the Spanish MINECO under grant TIN2012-37475-C02-01 (STraDa), and the Generalitat Valenciana under grant ISIC/2012/004 (AMIIS).Leiva, LA.; Alabau, V.; Romero Gómez, V.; Toselli, AH.; Vidal, E. (2015). Contex-aware gestures for mixed-initiative text editings UIs. Interacting with Computers. 27(6):675-696. https://doi.org/10.1093/iwc/iwu019S675696276Alabau V. Leiva L. A. Transcribing Handwritten Text Images with a Word Soup Game. Proc. Extended Abstr. Hum. Factors Comput. Syst. (CHI EA) 2012.Alabau V. Rodríguez-Ruiz L. Sanchis A. Martínez-Gómez P. Casacuberta F. 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The Usability and Learnability of Pen/Tablet Mode Inferencing

The inferred mode protocol uses contextual reasoning and local mediators to eliminate the need to access specic modes to perform draw, select, move and delete operations in a sketch interface. This thesis describe an observational experiment to understand the learn- ability, user preference and frequency of use of mode inferencing in a sketch appli- cation. Novel methodology is presented to study both quantitative and long term qualitative facets of mode inferencing. The experiment demonstrated that participants instructed in the in- terface features enjoyed fluid transitions between modes. As well, interaction techniques were not self-revealing: Participants who were not instructed in interaction techniques took longer to learn about inferred mode features and were more negative about the interaction techniques. Over multiple sketching sessions, as users develop expertise with the system, they combine inferred mode techniques to speed interaction, and frequently make use of scratch space on the display to retrain themselves and to tune their behaviors. Lastly, post- task interviews outline impediments to discoverability and how performance is affected by negative perceptions around computational intelligence. The results of this work inform the design of sketch interface techniques that incorporate noncommand features