HDS, a real-time multi-DSP motion estimator for MPEG-4 H.264 AVC high definition video encoding

International audienceH.264 AVC video compression standard achieves high compression rates at the cost of a high encoder complexity. The encoder performances are greatly linked to the motion estimation operation which requires high computation power and memory bandwidth. High definition context magnifies the difficulty of a real-time implementation. EPZS and HME are two well-known motion estimation algorithms. Both EPZS and HME are implemented in a DSP and their performances are compared in terms of both quality and complexity. Based on these results, a new algorithm called HDS for Hierarchical Diamond Search is proposed. HDS motion estimation is integrated in a AVC encoder to extract timings and resulting video qualities reached. A real-time DSP implementation of H.264 quarter-pixel accuracy motion estimation is proposed for SD and HD video format. Furthermore HDS characteristics make this algorithm well suited for H.264 SVC real-time encoding applications

Optimization of the motion estimation for parallel embedded systems in the context of new video standards

15 pagesInternational audienceThe effciency of video compression methods mainly depends on the motion compensation stage, and the design of effcient motion estimation techniques is still an important issue. An highly accurate motion estimation can significantly reduce the bit-rate, but involves a high computational complexity. This is particularly true for new generations of video compression standards, MPEG AVC and HEVC, which involves techniques such as different reference frames, sub-pixel estimation, variable block sizes. In this context, the design of fast motion estimation solutions is necessary, and can concerned two linked aspects: a high quality algorithm and its effcient implementation. This paper summarizes our main contributions in this domain. In particular, we first present the HME (Hierarchical Motion Estimation) technique. It is based on a multi-level refinement process where the motion estimation vectors are first estimated on a sub-sampled image. The multi-levels decomposition provides robust predictions and is particularly suited for variable block sizes motion estimations. The HME method has been integrated in a AVC encoder, and we propose a parallel implementation of this technique, with the motion estimation at pixel level performed by a DSP processor, and the sub-pixel refinement realized in an FPGA. The second technique that we present is called HDS for Hierarchical Diamond Search. It combines the multi-level refinement of HME, with a fast search at pixel-accuracy inspired by the EPZS method. This paper also presents its parallel implementation onto a multi-DSP platform and the its use in the HEVC context

Développement durable et gestion internationale : enjeux et perspectives d'avenir.

Développement durable et gestion internationale : enjeux et perspectives d'avenir. Texte d'introduction au numéro thématiqueCommerce international; Développement durable;

A flexible heterogeneous hardware/software solution for real-time high-definition H.264 motion estimation

International audienceThe MPEG-4 AVC/H.264 video compression standard introduces a high degree of motion estimation complexity. Quarter-pixel accuracy and variable block-size significantly enhance compression performances over previous standards, but increase computation requirements. Firstly, a DSP-based solution achieves real-time integer motion estimation. Nevertheless, fractional-pixel refinement is too computationally intensive to be efficiently processed on a software-based processor. Secondly, to address this restriction, a flexible and low complexity VLSI sub-pixel refinement coprocessor is designed. Thanks to an improved datapath, a high throughput is achieved with low logic resources. Finally, we propose a heterogeneous (DSP-FPGA) solution to handle real-time motion estimation with variable block-size and fractional-pixel accuracy for high-definition video. It combines efficiency and programmability. The flexibility offers complexity versus performance trade-offs. The system achieves motion estimation of 720p sequences at up to 60 frames per second

ReCIPH: Relational Coefficients for Input Partitioning Heuristic

International audienceWith the rapidly advancing improvements to the already successful Deep Learning artifacts, Neural Networks (NN) are poised to permeate a growing number of everyday applications, including ones where safety is paramount and, therefore, formal guarantees are a precious commodity. To this end, Formal Methods, a long-standing, mathematically-inspired field of research saw an effervescent outgrowth targeting NN and advancing almost as rapidly as AI itself. Without a doubt, the most challenging problem facing this new research direction is the scalability to the evergrowing NN models. This paper stems from this need and introduces Relational Coefficients for Input partitioning Heuristic (ReCIPH), accelerating NN analysis. Extensive experimentation is supplied to assert the added value to two different solvers handling several models and properties (coming, in part, from two industrial use-cases)

Unified understanding of intrinsic and extrinsic controls of dissolved organic carbon reactivity in aquatic ecosystems

Despite our growing understanding of the global carbon cycle, scientific consensus on the drivers and mechanisms that control dissolved organic carbon (DOC) turnover in aquatic systems is lacking, hampered by the mismatch between research that approaches DOC reactivity from either intrinsic (inherent chemical properties) or extrinsic (environmental context) perspectives. Here we propose a conceptual view of DOC reactivity in which the combination of intrinsic and extrinsic factors controls turnover rates and determines which reactions will occur. We review three major types of reactions (biological, photochemical, and flocculation) from an intrinsic chemical perspective and further define the environmental features that modulate the expression of chemically inherent reactivity potential. Finally, we propose hypotheses of how extrinsic and intrinsic factors together shape patterns in DOC turnover across the land-to-ocean continuum, underscoring that there is no intrinsic DOC reactivity without environmental context. By acknowledging the intrinsic–extrinsic control duality, our framework intends to foster improved modeling of DOC reactivity and its impact on ecosystem services.publishedVersio

Unified understanding of intrinsic and extrinsic controls of dissolved organic carbon reactivity in aquatic ecosystems

Despite our growing understanding of the global carbon cycle, scientific consensus on the drivers and mechanisms that control dissolved organic carbon (DOC) turnover in aquatic systems is lacking, hampered by the mismatch between research that approaches DOC reactivity from either intrinsic (inherent chemical properties) or extrinsic (environmental context) perspectives. Here we propose a conceptual view of DOC reactivity in which the combination of intrinsic and extrinsic factors controls turnover rates and determines which reactions will occur. We review three major types of reactions (biological, photochemical, and flocculation) from an intrinsic chemical perspective and further define the environmental features that modulate the expression of chemically inherent reactivity potential. Finally, we propose hypotheses of how extrinsic and intrinsic factors together shape patterns in DOC turnover across the land-to-ocean continuum, underscoring that there is no intrinsic DOC reactivity without environmental context. By acknowledging the intrinsic–extrinsic control duality, our framework intends to foster improved modeling of DOC reactivity and its impact on ecosystem services