摘要
针对多视环境下特征点提取计算耗时较长的问题,提出其并行实现方法。通过灰度共生矩阵构造纹理特征差异度,选取关键视点和消除冗余视点,采用Harris角点提取算法、团块检测算法,提取关键视点图像的特征点,利用关键视点选取及特征点提取过程存在的并行性,对算法进行并行实现。实验结果表明,该方法能有效地选取关键视点,在双核处理器上使平均加速比达到1.88。
Feature extraction in the multi-view environment is an important step in 3D reconstruction.However,it is a very time-consuming task.To accelerate the speed of extracting feature,this paper presents a parallel method to extract feature in the multi-view environment.The key views are selected by the texture feature discrepancy which is computed based on the grey level grows matrix.Harris corner detection algorithm and Blob detection algorithm are adopted to extract feature of the key view images.The method is parallelized by exploring the inherent parallelism of proposed procedures.Experimental results show that the method can select the key views efficiently,and the average speedup achieves 1.88 on a dual-core system.
出处
《计算机工程》
CAS
CSCD
2012年第1期182-184,共3页
Computer Engineering
基金
国家自然科学基金资助项目(61071173)
中国科学技术大学研究生创新基金资助项目
关键词
特征提取
并行算法
多视图像
3D重构
纹理特征
feature extraction
parallel algorithm
multi-view image
3D reconstruction
texture feature
