Dynamic Adaptive Point Cloud Streaming

High-quality point clouds have recently gained interest as an emerging form of representing immersive 3D graphics. Unfortunately, these 3D media are bulky and severely bandwidth intensive, which makes it difficult for streaming to resource-limited and mobile devices. This has called researchers to propose efficient and adaptive approaches for streaming of high-quality point clouds. In this paper, we run a pilot study towards dynamic adaptive point cloud streaming, and extend the concept of dynamic adaptive streaming over HTTP (DASH) towards DASH-PC, a dynamic adaptive bandwidth-efficient and view-aware point cloud streaming system. DASH-PC can tackle the huge bandwidth demands of dense point cloud streaming while at the same time can semantically link to human visual acuity to maintain high visual quality when needed. In order to describe the various quality representations, we propose multiple thinning approaches to spatially sub-sample point clouds in the 3D space, and design a DASH Media Presentation Description manifest specific for point cloud streaming. Our initial evaluations show that we can achieve significant bandwidth and performance improvement on dense point cloud streaming with minor negative quality impacts compared to the baseline scenario when no adaptations is applied.Comment: 6 pages, 23rd ACM Packet Video (PV'18) Workshop, June 12--15, 2018, Amsterdam, Netherland

Predictive power management for multi-core processors

textEnergy consumption by computing systems is rapidly increasing due to the growth of data centers and pervasive computing. In 2006 data center energy usage in the United States reached 61 billion kilowatt-hours (KWh) at an annual cost of 4.5 billion USD [Pl08]. It is projected to reach 100 billion KWh by 2011 at a cost of 7.4 billion USD. The nature of energy usage in these systems provides an opportunity to reduce consumption. Specifically, the power and performance demand of computing systems vary widely in time and across workloads. This has led to the design of dynamically adaptive or power managed systems. At runtime, these systems can be reconfigured to provide optimal performance and power capacity to match workload demand. This causes the system to frequently be over or under provisioned. Similarly, the power demand of the system is difficult to account for. The aggregate power consumption of a system is composed of many heterogeneous systems, each with a unique power consumption characteristic. This research addresses the problem of when to apply dynamic power management in multi-core processors by accounting for and predicting power and performance demand at the core-level. By tracking performance events at the processor core or thread-level, power consumption can be accounted for at each of the major components of the computing system through empirical, power models. This also provides accounting for individual components within a shared resource such as a power plane or top-level cache. This view of the system exposes the fundamental performance and power phase behavior, thus making prediction possible. This dissertation also presents an extensive analysis of complete system power accounting for systems and workloads ranging from servers to desktops and laptops. The analysis leads to the development of a simple, effective prediction scheme for controlling power adaptations. The proposed Periodic Power Phase Predictor (PPPP) identifies patterns of activity in multi-core systems and predicts transitions between activity levels. This predictor is shown to increase performance and reduce power consumption compared to reactive, commercial power management schemes by achieving higher average frequency in active phases and lower average frequency in idle phases.Electrical and Computer Engineerin

Multimedia delivery in the future internet

The term “Networked Media” implies that all kinds of media including text, image, 3D graphics, audio and video are produced, distributed, shared, managed and consumed on-line through various networks, like the Internet, Fiber, WiFi, WiMAX, GPRS, 3G and so on, in a convergent manner [1]. This white paper is the contribution of the Media Delivery Platform (MDP) cluster and aims to cover the Networked challenges of the Networked Media in the transition to the Future of the Internet. Internet has evolved and changed the way we work and live. End users of the Internet have been confronted with a bewildering range of media, services and applications and of technological innovations concerning media formats, wireless networks, terminal types and capabilities. And there is little evidence that the pace of this innovation is slowing. Today, over one billion of users access the Internet on regular basis, more than 100 million users have downloaded at least one (multi)media file and over 47 millions of them do so regularly, searching in more than 160 Exabytes1 of content. In the near future these numbers are expected to exponentially rise. It is expected that the Internet content will be increased by at least a factor of 6, rising to more than 990 Exabytes before 2012, fuelled mainly by the users themselves. Moreover, it is envisaged that in a near- to mid-term future, the Internet will provide the means to share and distribute (new) multimedia content and services with superior quality and striking flexibility, in a trusted and personalized way, improving citizens’ quality of life, working conditions, edutainment and safety. In this evolving environment, new transport protocols, new multimedia encoding schemes, cross-layer inthe network adaptation, machine-to-machine communication (including RFIDs), rich 3D content as well as community networks and the use of peer-to-peer (P2P) overlays are expected to generate new models of interaction and cooperation, and be able to support enhanced perceived quality-of-experience (PQoE) and innovative applications “on the move”, like virtual collaboration environments, personalised services/ media, virtual sport groups, on-line gaming, edutainment. In this context, the interaction with content combined with interactive/multimedia search capabilities across distributed repositories, opportunistic P2P networks and the dynamic adaptation to the characteristics of diverse mobile terminals are expected to contribute towards such a vision. Based on work that has taken place in a number of EC co-funded projects, in Framework Program 6 (FP6) and Framework Program 7 (FP7), a group of experts and technology visionaries have voluntarily contributed in this white paper aiming to describe the status, the state-of-the art, the challenges and the way ahead in the area of Content Aware media delivery platforms

TechNews digests: Jan - Nov 2009

TechNews is a technology, news and analysis service aimed at anyone in the education sector keen to stay informed about technology developments, trends and issues. TechNews focuses on emerging technologies and other technology news. TechNews service : digests september 2004 till May 2010 Analysis pieces and News combined publish every 2 to 3 month

Fingerprint Recognition Using Translation Invariant Scattering Network

Fingerprint recognition has drawn a lot of attention during last decades. Different features and algorithms have been used for fingerprint recognition in the past. In this paper, a powerful image representation called scattering transform/network, is used for recognition. Scattering network is a convolutional network where its architecture and filters are predefined wavelet transforms. The first layer of scattering representation is similar to sift descriptors and the higher layers capture higher frequency content of the signal. After extraction of scattering features, their dimensionality is reduced by applying principal component analysis (PCA). At the end, multi-class SVM is used to perform template matching for the recognition task. The proposed scheme is tested on a well-known fingerprint database and has shown promising results with the best accuracy rate of 98\%.Comment: IEEE Signal Processing in Medicine and Biology Symposium, 201