摘要
研究图像帧的准确定位检索问题。由于图像的语义特征与一般像素特征不同,包含图像固有属性、图像对象和人为意识三个特征,上述三个特征之间具有较大的逻辑无关性,造成以这三个特征为基础建立的语义检索模型很难形成统一的检索特征标准,多个特征的检索确认模式造成图像检索精度较低。为了避免上述缺陷,提出一种图像共现语义特征的关键帧定位技术,对计算机视觉图像进行分类处理,从而提取出与目标具有较强相关性的视觉图像,将获取的结果作为关键帧定位的基础图像。利用图像共现语义特征算法,进行关键帧定位处理。实验结果表明,改进算法进行关键帧定位处理,能够极大的提高关键帧定位的准确性,从而提高计算机视觉处理技术的性能。
The problem of image frames accurately positioning retrieval was researched in the paper. This paper put forward the semantic characteristics of key frame based on image co - occurrence positioning technology to classify the computer vision images, so as to extract visual images which have strong correlation with the target, and regard the obtained results as the basis image of key frames positioning. The semantic feature image co - occurrence algo- rithm was employed to localize the key frames. The experimental results show that the improved algorithm for key frame positioning processing can greatly improve the accuracy of key frame positioning, thereby improve the perform- ance of computer vision techniques.
出处
《计算机仿真》
CSCD
北大核心
2014年第2期419-422,共4页
Computer Simulation
基金
吉林省教育厅"十二五"科学技术研究基金资助项目(吉教科合字2012第404号)
关键词
共现语义特征
关键帧
定位技术
Co - occurrence of semantic features
Key frames
Positioning technology
