基于相关度和注意力聚焦的图像内容检索

基于内容的检索中对图像和视频帧的处理是以色彩、形状和纹理等为基本特征，这些特征在图像背景比较单一的情况下容易获得。一旦图像背景为色彩和纹理均很复杂的图像时，图像中目标的颜色和形状等特征就很难获得。若将从计算机视觉中引出的相关度和注意力聚焦两个概念用于从复杂背景图像中定位和选取最有关的信息，则能够有效地检索到最匹配的图像。本文通过对相关度和注意力聚焦两个概念的讨论，介绍了计算机视觉对基于内容检索的作用，尤其是在可视示例查询ＱＶＥ（ＱｕｅｒｙｂｙＶｉｓｕａｌＥｘａｍｐｌｅ）的情况下从大图像数据库中检索图像的情况

Image Content Retrieval Based on Relevance and Focus-of-attention

Color,shape and texture are the essential features for image and video frame processing in content based retrieval.It is easy to obtain these features when the background of the image is simple.Once it becomes complicated color and texture ,it is difficult to get such features.Two concepts,namely:relevance and focus of attention quoted from the computer vision can be used to locate and select the most related imformation in the image with a complicated background and the best matched image can be efficiently retrieved .In this paper we discuss these two concepts and discribe their roles in image retrieval,especially in the case of QVE(Query by Visual Example).