Study of techniques for motion image retrieval based on motion information

基于运动信息的运动图像检索技术研究

基本信息

批准号：
12650367
负责人：
YOSHIDA Toshiyuki
金额：
$ 1.41万
依托单位：
Tokyo Institute of Technology
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2000
资助国家：
日本
起止时间：
2000 至 2001
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-12650367/
关键词：
Motion image MPEG Motion vector Retrieval MPEG

项目摘要

In this research, we aimed at developing techniques for retrieving MPEG-encoded motion images based mainly on motion information. The following are the results of the research :1. We selected a sketch-based, feature-based model for the target retrieval system. For the feature values, we used histograms of the average color and motion vector for each macroblock.2. Taking the histogram of the color and motion vector in a video scene drops their spatio-temporal distribution information. In order to maintain the information as well as to speed up the retrieval, we proposed a hierarchical matching technique.3. We obtained the result that a representation of motion vectors in a kind of polar coordinate system rather than in the orthogonal coordinate gives an efficient similarity measure for motion vectors which well match human visual characteristics. We then actually applied the similarity measure to the motion image retieval and confirmed its efficiency over the conventional orthogonal coordinate representation.4. The matching algorithm based on motion vector and color histograms requires the users to input all the information with respect to the foreground and background objects and camera motions for the target scene. Since this is, however, not always possible, we have revised the algorithm in such a way that a histogram matching can be performed without knowing all the information for the target scene.5. We combined all the fundamental algorithms developed in this research to make a prototype retrieval system for motion images. Numbers of retrieval experiments on the prototype system have confirmed that the system can search for scences that are close to user's target scenes.

在这项研究中，我们的目标是开发主要基于运动信息检索 MPEG 编码运动图像的技术。研究结果如下： 1．我们为目标检索系统选择了基于草图、基于特征的模型。对于特征值，我们使用每个宏块的平均颜色和运动矢量的直方图。2．获取视频场景中的颜色和运动矢量的直方图会丢弃它们的时空分布信息。为了保持信息并加快检索速度，我们提出了分层匹配技术。 3．我们得到的结果是，在一种极坐标系中而不是在正交坐标系中表示运动矢量，可以为运动矢量提供有效的相似性度量，很好地匹配人类视觉特征。然后我们实际将相似性度量应用于运动图像检索并确认其相对于传统正交坐标表示的效率。 4．基于运动矢量和颜色直方图的匹配算法要求用户输入目标场景的前景和背景物体以及相机运动的所有信息。然而，由于这并不总是可能的，因此我们修改了算法，使得可以在不知道目标场景的所有信息的情况下执行直方图匹配。5。我们结合了本研究中开发的所有基本算法，制作了运动图像检索系统的原型。在原型系统上进行的大量检索实验证实，该系统能够搜索到与用户目标场景接近的场景。