Playing immersive games on the REVERIE platform

REVERIE (REal and Virtual Engagement in Realistic Immersive Environments) [1] is a multimedia and multimodal framework, which supports the creation of immersive games. The framework supports the creation of games integrating technologies such as 3D spatial audio, detection of the player’s body movement using Kinect and WIMO sensors, NPCs (Non-Playable Characters) with advanced AI capabilities featuring various levels of representation and gameplay into an immersive 3D environment. A demonstration game was developed for REVERIE, which is an adapted version of the popular Simon Says game. In the REVERIE version, a player tries to follow physical instructions issued by two autonomous agents with different degrees of realism. If a player follows a physical instruction correctly, they are awarded one point. If not, they are deducted one point. This paper presents a technical overview of the game technologies integrated in the Simon Says demo and its evaluation by players with variable computer literacy skills. Finally the potential of REVERIE as an immersive framework for gaming is discussed, followed by recommendations for improvements in future versions of the framework.

Dithen: A Computation-as-a-Service Cloud Platform For Large-Scale Multimedia Processing

We present Dithen, a novel computation-as-a-service (CaaS) cloud platform specifically tailored to the parallel ex-ecution of large-scale multimedia tasks. Dithen handles the upload/download of both multimedia data and executable items, the assignment of compute units to multimedia workloads, and the reactive control of the available compute units to minimize the cloud infrastructure cost under deadline-abiding execution. Dithen combines three key properties: (i) the reactive assignment of individual multimedia tasks to available computing units according to availability and predetermined time-to-completion constraints; (ii) optimal resource estimation based on Kalman-filter estimates; (iii) the use of additive increase multiplicative decrease (AIMD) algorithms (famous for being the resource management in the transport control protocol) for the control of the number of units servicing workloads. The deployment of Dithen over Amazon EC2 spot instances is shown to be capable of processing more than 80,000 video transcoding, face detection and image processing tasks (equivalent to the processing of more than 116 GB of compressed data) for less than $1 in billing cost from EC2. Moreover, the proposed AIMD-based control mechanism, in conjunction with the Kalman estimates, is shown to provide for more than 27% reduction in EC2 spot instance cost against methods based on reactive resource estimation. Finally, Dithen is shown to offer a 38% to 500% reduction of the billing cost against the current state-of-the-art in CaaS platforms on Amazon EC2 (Amazon Lambda and Amazon Autoscale). A baseline version of Dithen is currently available at dithen.com.