Answer Set Programming Modulo `Space-Time'

We present ASP Modulo `Space-Time', a declarative representational and computational framework to perform commonsense reasoning about regions with both spatial and temporal components. Supported are capabilities for mixed qualitative-quantitative reasoning, consistency checking, and inferring compositions of space-time relations; these capabilities combine and synergise for applications in a range of AI application areas where the processing and interpretation of spatio-temporal data is crucial. The framework and resulting system is the only general KR-based method for declaratively reasoning about the dynamics of `space-time' regions as first-class objects. We present an empirical evaluation (with scalability and robustness results), and include diverse application examples involving interpretation and control tasks

MASCOT : metadata for advanced scalable video coding tools : final report

The goal of the MASCOT project was to develop new video coding schemes and tools that provide both an increased coding efficiency as well as extended scalability features compared to technology that was available at the beginning of the project. Towards that goal the following tools would be used: - metadata-based coding tools; - new spatiotemporal decompositions; - new prediction schemes. Although the initial goal was to develop one single codec architecture that was able to combine all new coding tools that were foreseen when the project was formulated, it became clear that this would limit the selection of the new tools. Therefore the consortium decided to develop two codec frameworks within the project, a standard hybrid DCT-based codec and a 3D wavelet-based codec, which together are able to accommodate all tools developed during the course of the project

In-layer multi-buffer framework for rate-controlled scalable video coding

Temporal scalability is supported in scalable video coding (SVC) by means of hierarchical prediction structures, where the higher layers can be ignored for frame rate reduction. Nevertheless, this kind of scalability is not totally exploited by the rate control (RC) algorithms since the hypothetical reference decoder (HRD) requirement is only satisfied for the highest frame rate sub-stream of every dependency (spatial or coarse grain scalability) layer. In this paper we propose a novel RC approach that aims to deliver several HRD-compliant temporal resolutions within a particular dependency layer. Instead of using the common SVC encoder configuration consisting of a dependency layer per each temporal resolution, a compact configuration that does not require additional dependency layers for providing different HRD-compliant temporal resolutions is proposed. Specifically, the proposed framework for rate-controlled SVC uses a set of virtual buffers within a dependency layer so that their levels can be simultaneously controlled for overflow and underflow prevention while minimizing the reconstructed video distortion of the corresponding sub-streams. This in-layer multi-buffer approach has been built on top of a baseline H.264/SVC RC algorithm for variable bit rate applications. The experimental results show that our proposal achieves a good performance in terms of mean quality, quality consistency, and buffer control using a reduced number of layers.This work has been partially supported by the National Grant TEC2011-26807 of the Spanish Ministry of Science and Innovation.Publicad