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   image and video retrieval 的翻译结果: 查询用时:0.158秒
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image and video retrieval
相关语句
  图像及视频检索
     Content-Based Image and Video Retrieval
     基于内容的图像及视频检索
短句来源
     Content based image and video retrieval is a active field of research in computer vision and multimedia database management.
     基于内容的图像及视频检索是当前计算机视觉、多媒体数据库管理等研究领域的热点之一。
短句来源
     Face detection is an important task in face recognition and content-based image and video retrieval.
     人脸检测是人脸识别与图像及视频检索的一项重要任务。
短句来源
  图像视频检索
     Investigation of the Influence of Compressed-Domain DCT Coefficients on Image and Video Retrieval
     压缩域DCT系数对图像视频检索影响的研究
短句来源
     Study and application on image and video retrieval
     图像视频检索的研究和应用
短句来源
     We use the method in our implementation of MPEG4 coding and decoding program,and bring forward a fast arithmetic based on DC+2AC to raise the efficiency of compressed-domain image and video retrieval.
     随后提出了一种提高压缩域图像视频检索效率的方法,进而针对IntelX86处理器平台改进了DC+2AC的快速算法。
短句来源
  图像和视频检索
     The article commences from the characteristics of content-based multimedia information retrieval analysis,have discussed content-based image and video retrieval in common use key technique,have elaborated the problem that multimedia information retrieval needs solve further.
     文章从基于内容的多媒体信息检索的特点分析入手 ,论述了基于内容的图像和视频检索常用关键技术 ,阐述了多媒体信息检索需要进一步解决的问题
短句来源
     Research and Implementation of Content-based Image and Video Retrieval Techniques
     基于内容的图像和视频检索技术研究及其系统实现
短句来源
     Ear detection is an important task in ear recognitionand content- based image and video retrieval.
     人耳检测是人耳识别以及基于内容的图像和视频检索的一项重要任务。
短句来源
     With the rapid development of multimedia and network techniques, efficient and effective image and video retrieval becomes more and more important due to teeming of vast image and video media in many coding formats.
     随着多媒体技术和网络技术的迅猛发展,巨量的图像和视频信息以各种编码形式不断涌现,使得有效的图像和视频检索变得日益重要。
短句来源
     But there still are a lot of problems needed to be resolved in the content-based image and video retrieval at present.
     但是到目前为止,基于内容的图像和视频检索还存在很多问题有待解决。
短句来源
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  “image and video retrieval”译为未确定词的双语例句
     Study and Application on Digital Image and Video Retrieval
     数字图象视频检索的研究和应用
短句来源
     So, the Content Based Image and Video Retrieval technology comes into being and becomes an important research area in multimedia retrieval and image processing.
     由此,基于内容的图象和视频检索技术得到了越来越多的重视,成为了多媒体信息检索和图象处理领域中的重要研究方向。
短句来源
     Comparing with image and video retrieval, audio retrieval study is behindhand.
     相对于日益成熟的图像与视频检索,音频检索相对滞后。
短句来源
     In section l,both the job we have done and the research state of content-based image and video retrieval are described.
     第一部分论述了基于内容的图像、视频检索的研究现状和本课题所做的主要工作。
短句来源
     Image and video are the most intuitionistic information in multimedia. Image and video retrieval and query is an important aspect in the multimedia processing.
     图像、视频作为多媒体中最直观、最形象的内容,对它们的检索和查询是多媒体信息处理的一个重要方面。
短句来源
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  image and video retrieval
Will be able to explain the main steps in the history, state of the art, and future of semantic image and video retrieval 2.
      
Trends and Advances in Content-Based Image and Video Retrieval, L.
      
Several content-based image and video retrieval systems use region-based search methods.
      
In this tutorial we will discuss the history, the state of art, and the future of semantic image and video retrieval.
      
In Proceedings of the International Conference on Image and Video Retrieval, 2003.
      
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Face detection is an important task in face recognition and content based image and video retrieval. The difficulty in training a face pattern classifier as face detector is due to the diversity and complexity of non face patterns compared with face patterns. In this paper, we propose a subspace method for downsizing the training space via template matching filtering. Two types of templates, eyes in whole and face itself from an average face of a set of mugshot photos, are used in template matching...

Face detection is an important task in face recognition and content based image and video retrieval. The difficulty in training a face pattern classifier as face detector is due to the diversity and complexity of non face patterns compared with face patterns. In this paper, we propose a subspace method for downsizing the training space via template matching filtering. Two types of templates, eyes in whole and face itself from an average face of a set of mugshot photos, are used in template matching for coarse filtration. Only when both eyes in whole template matching and face template matching are over corresponding thresholds, a candidate window is regarded as in the subspace. In this template matching constrained subspace, a bootstrap method is used to collect non face samples for SVM training, which greatly reduces the complexity of training SVM. The face detector SVM is trained by John Platt's Sequential Minimal Optimization (SMO) algorithm. During the detection procedure, an image and its scaled images are scanned, each candidate window will first be evaluated by both eyes in whole template matching and face template matching, and when both are over corresponding thresholds that candidate will be passed to the SVM classifier for the final decision. The detection results over all scales are then merged into final face detection output by way of fusion that keeps only the maximum one when overlap happens. In this way the training becomes much easier and the speed is improved to be used in practical applications. Experimental results with very promising performance compared with some well known existing detectors on both test sets of our own and the CMU's test set demonstrate its effectiveness.

人脸检测是人脸识别与基于内容的图像及视频检索的一项重要任务 .由于非人脸样本相对于人脸样本的多样性和复杂性 ,使得人脸模式分类器的训练十分困难 .该文提出了一种将模板匹配与支持矢量机 (SVM)相结合的人脸检测算法 .算法首先使用双眼 -人脸模板对进行粗筛选 ,然后使用 SVM分类器进行分类 .在模板匹配限定的子空间内采用“自举”方法收集“非人脸”样本训练 SVM,有效地降低了训练的难度 .实验结果的对比数据表明 ,该算法是十分有效的

Content based image and video retrieval is a active field of research in computer vision and multimedia database management. This paper reviews the current state of the art in content based image and video retrieval. For still images, we focus on the retrieval methods based on interactive feedback as well as image feature information such as color, texture, shape, region and object. For video sequences, we introduce such techniques as shot detection, representation of shot...

Content based image and video retrieval is a active field of research in computer vision and multimedia database management. This paper reviews the current state of the art in content based image and video retrieval. For still images, we focus on the retrieval methods based on interactive feedback as well as image feature information such as color, texture, shape, region and object. For video sequences, we introduce such techniques as shot detection, representation of shot content, semantic scene description. Finally, the difficulty and the future work in this research field is pointd out.

基于内容的图像及视频检索是当前计算机视觉、多媒体数据库管理等研究领域的热点之一。较系统地介绍了该研究领域的现状。对于静态图像 ,主要介绍了基于颜色、纹理、形状、区域或目标等低级图像特征信息的检索以及基于交互式反馈的检索方法 ;对于视频序列 ,则介绍了镜头检测、镜头内容表示、场景的语义描述等技术。最后指出了该研究领域存在的难点及今后的工作。

This is the eighth in the survey series of the yearly bibliographies on image engineering in China. The purpose of this survey work is mainly to capture the up-to-date development of image engineering in China, to provide a convenient means of literature searching facility for readers working in related areas, and to supply a useful reference for the editors of journals and potential authors of papers. Considering the wide distribution of related publications in China, 545 image engineering research and technique...

This is the eighth in the survey series of the yearly bibliographies on image engineering in China. The purpose of this survey work is mainly to capture the up-to-date development of image engineering in China, to provide a convenient means of literature searching facility for readers working in related areas, and to supply a useful reference for the editors of journals and potential authors of papers. Considering the wide distribution of related publications in China, 545 image engineering research and technique references are selected carefully from 2426 research papers published in a set of 15 Chinese journals. These 15 journals are considered as important journals in which papers concerning image engineering have higher quality and are relatively concentrated. Those selected references are classified first into 5 categories (image processing, image analysis, image understanding, technique application and survey), and then into 21 classes according to their main contents. Some analysis and discussions about the statistics made on the classification results are also presented. This work shows a general and off-the-shelf picture of the various progresses of image engineering in China. In 2002, the number of research papers in image engineering has a considerable increase. Except "traditional" image segmentation and image coding, new research areas, such as image formation techniques, digital image watermarking, human face and organ detection, image matching and information fusion, and image and video retrieval are still in fast progresses.

该文是关于中国图象工程的年度文献综述系列之八 .为了使国内广大从事图象工程研究和图象技术应用的科技人员能够较全面地了解国内图象工程研究和发展的现状 ,并能够方便地查询有关文献 ,现从国内 15种有关图象工程重要中文期刊 2 0 0 2年出版的共 10 8期上发表的 2 4 2 6篇学术研究和技术应用文献中 ,选取出 5 4 5篇属于图象工程领域的文献 ,然后根据各文献的主要内容将其分别归入图象处理、图象分析、图象理解、技术应用和综述 5个大类 ,又进一步分入 2 1个小类 ,并在此基础上进行了文献统计和分析 .由统计分析结果可见 ,中国图象工程在2 0 0 2年又有了许多新进展 ,除总的文献数量有较大增加 ,图象分割和图象编码仍有许多研究成果外 ,近年来的几个新的研究热点 ,如成像技术、图象数字水印、人脸和器官检测、图象匹配融合、图象和视频检索等继续保持了快速发展的势头 .

 
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