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    • 4. 发明申请
    • Method and apparatus for performing multiple description motion compensation using hybrid predictive codes
    • 使用混合预测码执行多描述运动补偿的方法和装置
    • US20060093031A1
    • 2006-05-04
    • US10523434
    • 2003-07-24
    • Mihaela Van Der SchaarDeepak Turaga
    • Mihaela Van Der SchaarDeepak Turaga
    • H04N11/04H04N11/02H04N7/12H04B1/66
    • H04N19/61
    • An improved multiple description coding (MDC) method and apparatus is provided which extends multi-description motion compensation (MDMC) by allowing for multi-frame prediction and is not limited to only I and P frames. Further, the coding method of the invention extends MDMC for use with any conventional predictive codec, such as, for example, MPEG2/4 and H.26L. The improved MDC permits the use of any conventional predictive coder for use as a top and bottom predictive encoder. Further, the top and bottom predictive coders can advantageously include B-frames and multiple prediction motion compensation. Still further, any of the top, middle and bottom predictive encoders can be a scalable encoder (e.g., FGS-like or data-partitioning like where the motion vectors (MVs) are sent first, temporal scalability etc.).
    • 提供了一种改进的多描述编码(MDC)方法和装置,其通过允许多帧预测来扩展多描述运动补偿(MDMC),并且不限于仅I帧和P帧。 此外,本发明的编码方法扩展了MDMC以用于任何常规的预测编解码器,例如MPEG2 / 4和H.26L。 改进的MDC允许使用任何常规的预测编码器用作顶部和底部预测编码器。 此外,顶部和底部预测编码器可以有利地包括B帧和多个预测运动补偿。 另外,顶部,中间和底部预测编码器中的任何一个可以是可伸缩的编码器(例如,像运动矢量(MV)首先被发送,时间可伸缩性等那样的类似FGS或数据分区)。
    • 7. 发明申请
    • Resource adaptive spectrum estimation of streaming data
    • 流数据资源自适应频谱估计
    • US20070223598A1
    • 2007-09-27
    • US11389344
    • 2006-03-24
    • Deepak TuragaMichail VlachosPhilip Yu
    • Deepak TuragaMichail VlachosPhilip Yu
    • H04L27/00
    • G06F17/141
    • Streaming environments typically dictate incomplete or approximate algorithm execution, in order to cope with sudden surges in the data rate. Such limitations are even more accentuated in mobile environments (such as sensor networks) where computational and memory resources are typically limited. Introduced herein is a novel “resource adaptive” algorithm for spectrum and periodicity estimation on a continuous stream of data. The formulation is based on the derivation of a closed-form incremental computation of the spectrum, augmented by an intelligent load-shedding scheme that can adapt to available CPU resources. Experimentation indicates that the proposed technique can be a viable and resource efficient solution for real-time spectrum estimation.
    • 流环境通常会指示不完整或近似算法执行,以应对数据速率的突然增加。 在计算和存储资源通常受限制的移动环境(如传感器网络)中,这种限制更加突出。 这里介绍的是一种用于连续数据流的频谱和周期估计的新型“资源自适应”算法。 该公式基于频谱的闭合增量计算的推导,通过可以适应可用CPU资源的智能加载开放方案来增强。 实验表明,提出的技术可以成为实时频谱估计的可行且资源有效的解决方案。