Threshold‐Based Camera Motion Characterization of MPEG Video

We propose an efficient scheme for camera motion characterization in MPEG‐compressed video. The proposed scheme detects six types of basic camera motions through threshold‐based qualitative interpretation, in which fixed thresholds are applied to motion model parameters estimated from MPEG motion vectors (MVs). The efficiency and robustness of the scheme are validated by the experiment with real compressed video sequences.     

压缩域图像检索技术的研究

从检索和压缩相互结合的角度出发,针对现有压缩标准(如JPEG、MPEG、JPEG2000等),对基于DCT和DWT压缩域的检索技术进行了深入研究,提出了一系列新技术.实验结果表明,这种压缩和检索相互结合的研究思路是高效可行的,为进一步提高多媒体应用系统的整体性能奠定了坚实基础.     

弧面分度凸轮机构分析及其虚拟样机技术的发展

评述了弧面凸轮机构的现状及目前设计中存在的问题,提出了弧面凸轮机构分析的基本方法,介绍了弧面凸轮机构在自动换刀装置中的应用.并指出虚拟样机技术在弧面凸轮机构设计和研究中的应用及其发展趋势.     

凸轮分度装置分度精度、停留精度检测系统

分度精度和停留精度是凸轮分度装置的重要性能指标,本文建立了以这两个参数为主测参数的凸轮分度装置检测系统,文中合理的选择了检测原理、传感器,并以对传感器的信号性质的分析为基础,配置了合理的系统硬件,设计了信号处理的方法,最后通过实验结果,说明本检测系统的适用性。     

差动分度过程中的角度补偿浅析

通过理论以及具体实例的计算，分析了利用分度头进行差动分度的角度补偿原理，并以正反两个方向的角度补偿计算，揭示了差动分度的结果与假设等分分数的无关性。     

二进制翻译后端指令分级索引策略

随着硬件平台的多元化,软件兼容性问题日益突出,二进制翻译技术是解决软件兼容性问题的重要手段.鉴于二进制翻译系统大部分执行时间消耗在后端指令的查找和执行过程中,高效的指令索引策略可以减少系统的指令查找开销,提高系统的整体效率.在对二进制翻译系统后端指令局部性特征进行统计分析的基础上,设计了一种能充分挖掘现代计算机系统硬件性能的二进制翻译指令分级索引策略.该策略结合二进制翻译系统后端指令特殊的局部性特征,使用针对性的替换算法对后端指令进行缓存,降低了系统的指令查找开销.在引入了LIIS索引策略后,开源二进制翻译系统QEMU的后端指令查找时间减少了70％,整个系统执行效率提高了15％.     

汉语自动分词词典新机制—词值哈希机制

汉语词典查询是中文信息处理系统的重要基础部分, 对系统效率有重要的影响. 国内自80年代中后期就开展了中文分词词典机制的研究, 为了提高现有基于词典的分词机制的查询效率, 对于词长不超过4字的词提出了一种全新的分词词典机制——基于汉字串进制值的拉链式哈希机制即词值哈希机制. 对每个汉字的机内码从新编码, 利用进制原理, 计算出一个词语的词值, 建立一个拉链式词值哈希机制, 从而提高查询匹配速度.     

基于PSNR空域量化索引调制水印参数定量估算

量化索引调制方法是常用的水印嵌入和信息隐藏方法,量化步长是该方法中决定嵌入深度的参量,目前往往是通过反复试验方法确定该参量的取值,因此影响水印嵌入速度.针对此问题,以抖动量化调制方法为例,根据量化误差的分布情况给出了基于量化步长的量化误差定量估算;以该定量估算为基础,以空域像素为量化系数推导出了量化步长、水印数据量与PSNR之间的定量关系式.实验结果显示,在相同情况下通过实验测得的PSNR值和定量关系式计算的PSNR值基本一致,验证了推导的定量关系式的正确性.     

Multi-Modal Dialog Scene Detection Using Hidden Markov Models for Content-Based Multimedia Indexing

A class of audio-visual data (fiction entertainment: movies, TV series) is segmented into scenes, which contain dialogs, using a novel hidden Markov model-based (HMM) method. Each shot is classified using both audio track (via classification of speech, silence and music) and visual content (face and location information). The result of this shot-based classification is an audio-visual token to be used by the HMM state diagram to achieve scene analysis. After simulations with circular and left-to-right HMM topologies, it is observed that both are performing very good with multi-modal inputs. Moreover, for circular topology, the comparisons between different training and observation sets show that audio and face information together gives the most consistent results among different observation sets.     

An encoding-based dual distance tree high-dimensional index

The paper proposes a novel symmetrical encoding-based index structure, which is called EDD-tree （for encoding-based dual distance tree）, to support fast k-nearest neighbor （k-NN） search in high-dimensional spaces. In the EDD-tree, all data points are first grouped into clusters by a k-means clustering algorithm. Then the uniform ID number of each data point is obtained by a dual-distance-driven encoding scheme, in which each cluster sphere is partitioned twice according to the dual distances of start- and centroid-distance. Finally, the uniform ID number and the centroid-distance of each data point are combined to get a uniform index key, the latter is then indexed through a partition-based B^＋-tree. Thus, given a query point, its k-NN search in high-dimensional spaces can be transformed into search in a single dimensional space with the aid of the EDD-tree index. Extensive performance studies are conducted to evaluate the effectiveness and efficiency of our proposed scheme, and the results demonstrate that this method outperforms the state-of-the-art high-dimensional search techniques such as the X-tree, VA-file, iDistance and NB-tree, especially when the query radius is not very large.