图 书 馆
图像搜索的未来The Future of Image Search |
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| 课程网址: | http://videolectures.net/kdd08_malik_fis/ |
| 主讲教师: | Jitendra Malik |
| 开课单位: | 加州大学伯克利分校 |
| 开课时间: | 2008-09-26 |
| 课程语种: | 英语 |
| 中文简介: |  Internet上有数十亿张图像。如今，搜索所需的图像主要基于文本数据，例如文件名或网页上的关联文本。图像内容使用不多。这有充分的理由。基于内容的图像检索领域出现在1990年代，主要集中在颜色和纹理提示上。这些模型比形状更容易建模，但结果却没有最初希望的有用。我将回顾计算机视觉社区在视觉对象识别领域的一些最新进展，这些进展具有更大的前景。这些方法的核心是更好的图像形状特征，机器学习技术的进步以及大量训练数据的可用性。 |
| 课程简介: | There are billions of images on the Internet. Today, searching for a desired image is largely based on textual data such as filename or associated text on the web page; not much use is made of the image content. There are good reasons for this. The field of content-based image retrieval, which emerged during the 1990s, focused primarily on color and texture cues. These were easier to model than shape, but they turned out to be much less useful than originally hoped. I shall review some of the recent developments in the field of visual object recognition in the computer vision community that offer greater promise. Much better image features for characterizing shape, advances in machine learning techniques, and the availability of large amounts of training data lie at the heart of these approaches. |
| 关 键 词: | 图像搜索; 文本数据; 计算机视觉社区 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2021-01-27：nkq |
| 最后编审: | 2021-03-10：zyk |
| 阅读次数: | 42 |