An augmented reality interface to contextual information

An Attitude-Based Reasoning Strategy to Enhance Interaction with Augmented Objects

“…Vision-based techniques, based on image analysis and pattern recognition, are usually slower and too heavy to be directly handled in the device. When applied to IoT, these systems should handle a broad database of objects to automatically recognize real instances [7], Sensor-based strategies rely on GPS and inertial mobile technology when available. This approach automates service triggering without user collaboration, but it does not work properly when indoors (GPS signal is not available and inertial technology are affected by, e.g., metallic furniture).…”

“…This work is further extended in [11], where historical records of user-device interaction are analysed in order to enhance the recommendation; a genetic algorithm is used in order to adapt the recommendation process to the user's circumstances. Equipped with special gadgets, the researches of [7] are able to determine where the user is looking at, exploiting this 'gaze tracking system' for enhancing the recommendation process. Of course, user's http://www.wikitude.com (present and past) location can be also used as an input factor for recommendation [2][5] [7].…”

“…Equipped with special gadgets, the researches of [7] are able to determine where the user is looking at, exploiting this 'gaze tracking system' for enhancing the recommendation process. Of course, user's http://www.wikitude.com (present and past) location can be also used as an input factor for recommendation [2][5] [7].…”

“…Several projects propose to (de)emphasize the overlapped images by changing their characteristics (colour, shape, size, etc.) in order to adapt them to the user context [2][12] [13], Of course, not only images can be adapted, but also text [7] or even sounds [5],…”

Editorial: special issue on augmented reality

“…They also use gesture-based interaction to enable touch sensing and browsing through the document stack. Finally, the (Ajanki et al 2011) paper explores how to develop context-sensitive interaction techniques. Using position and gaze sensing, their system can automatically infer user's interest in people and topics, and display AR content reflecting their interest and so support implicit rather than explicit interaction.…”