一种基于稀疏表示的羽绒目标检测与跟踪算法

Yanqiu Wang, Xiaofei Yan, Wei Zhang
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引用次数: 3

摘要

羽毛和羽绒制品越来越受欢迎。近年来,研究团队利用计算机对其进行了自动检测和识别。为了提高羽毛羽绒类别的识别率,本文提出了一种基于图像的目标羽绒图像检测自适应稀疏表示与跟踪方法,利用目标检测来确定羽毛羽绒类别。首先,经过研究,提出了改进的自适应稀疏表示理论,并在对图像进行相关特征研究后,将自适应稀疏表示理论和多尺度几何分析理论应用到图像识别算法中。该研究将构建一种新的自适应稀疏表达理论体系,提高图像识别羽毛的鲁棒性,促进目标跟踪技术的创新。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Algorithm of Feather and Down Target Detection and Tracking Method Based on Sparse Representation
Feather and down products are becoming more and more popular. In recent years, the research team has done the down automatic detection and recognition by computer. In order to raise the recognition rate of feather and down category, in the paper a goal down image detection adaptive sparse representation and tracking method based on image is proposed, and target detection is used to determine the feather and down category. First of all, after the study, proposed improved adaptive sparse expression theory, and related features in the study of down on the image, the adaptive sparse representation theory and the multi-scale geometric analysis theory is applied to image recognition algorithm. The research will build a new adaptive sparse expression theory system, improve the robustness of the feather of image recognition, and will promote the target tracking technology innovation.
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