ARIA: an adaptive and programmable media-flow architecture for interactive arts
Proceedings of the 12th annual ACM international conference on Multimedia
Confidence-driven early object elimination in quality-aware sensor workflows
DMSN '05 Proceedings of the 2nd international workshop on Data management for sensor networks
Optimization of media processing workflows with adaptive operator behaviors
Multimedia Tools and Applications
Performance Analysis of the ARIA Adaptive Media Processing Workflows using Colored Petri Nets
Electronic Notes in Theoretical Computer Science (ENTCS)
Ozone: continuous state-based media choreography system for live performance
Proceedings of the international conference on Multimedia
Modular design of media retrieval workflows using ARIA
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
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Recently, we introduced a novel ARchitecture for Interactive Arts (ARIA) middleware that processes, filters, and fuses sensory inputs and actuates responses in real-time while providing various Quality of Service (QoS) guarantees. The objective of ARIA is to incorporate realtime, sensed, and archived media and audience responses into live performances, on demand. An ARIA media workflow graph describes how the data sensed through media capture devices will be processed and what audio-visual responses will be actuated. Thus, each data object streamed between ARIA processing components is subject to transformations, as described by a media workflow graph. The media capture and processing components, such as media filters and fusion operators, are programmable and adaptable; i.e, the delay, size, frequency, and quality/precision characteristics of individual operators can be controlled via a number of parameters. In [1, 4, 5], we developed static and dynamic optimization algorithms which maximize the quality of the actuated responses, minimize the corresponding delay and the resource usage. In this demonstration, we present the ARIA GUI and the underlying kernel. More specifically, we describe how to design a media processing workflow, with adaptive operators, using the ARIA GUI and how to use the various optimization and adaptation alternatives provided by the ARIA kernel to execute media processing workflows.