This paper presents an experimental study of spatial sound usefulness in searching and navigating through augmented reality environments. Participants were asked to find three objects hidden within no-sound and spatial sound AR environments. The experiment showed that the participants of the spatialized sound group performed faster and more efficiently than working in nosound configuration. What is more, 3D sound was a valuable cue for navigation in AR environment. The collected data suggest that the use of spatial sound in AR environments can be a significant factor in searching and navigating for hidden objects within indoor AR scenes. To conduct the experiment, the CARE approach was applied, while its CARL language was extended with new elements responsible for controlling audio in 3D space.
The paper presents the concept of dynamic Contextual Augmented Reality Environments (CARE), in which augmentation presented to users is dynamically constructed based on four semantically described elements. The first element is the user's context (preferences, privileges, location, time, device's capabilities). The second element is a set of trackables -visual markers representing real world objects that can be augmented for a given user in a given context. The third element are content objects, representing interactive 2D and 3D multimedia content including video sequences and sounds to be presented on the trackables. The last one is a description of a user interface, which may be specific to a concrete device or application and which indicates the forms of information presentation and interaction available to a user. *
The paper presents a method of dynamic composition of interactive augmented reality (AR) scenes based on distributed data sources and depending on the context. For this purpose, a novel declarative language for modelling ubiquitous, contextual AR environments is employed. The language, called CARL -Contextual Augmented Reality Language, enables modularisation of the structure of AR scenes and the presented AR content. CARL separates specification of three categories of entities constituting an AR environment -trackable markers, content objects and interfaces. Particular entities may be selectively added to an AR scene, which makes the language flexible and particularly well suited for building dynamic AR systems.
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