一种基于改进NMS的牛脸检测方法

doi:10.3969/j.issn.1006-2475.2019.07.008

计算机与现代化

一种基于改进NMS的牛脸检测方法

(西南交通大学电气工程学院，四川成都611756)

收稿日期:2019-01-07 出版日期:2019-07-05 发布日期:2019-07-08
作者简介:苟先太（1971-），男，四川绵阳人，副教授，硕士生导师，博士，研究方向：计算机网络，模式识别，E-mail: gouxiantai@home.swjtu.edu.cn; 通信作者：黄巍（1995-），男，四川成都人，硕士研究生，研究方向：计算机视觉，深度学习，E-mail: huangwei_9521@163.com; 刘琪芬（1994-），女，云南曲靖人，硕士研究生，研究方向：智能信息处理，E-mail: 1622680696@qq.com。
基金资助:
四川省重大科技专项项目(18ZDZX0162); 四川省重点研发项目(2017GZ0159)

A Cattle Face Detection Method Based on Improved NMS

(School of Electrical Engineering, Southwest Jiaotong University, Chengdu 611756, China)

Received:2019-01-07 Online:2019-07-05 Published:2019-07-08

摘要/Abstract

摘要： 针对牲畜牛身份认证的多牛脸检测场景，本文给出一种基于改进Faster R-CNN的牛脸检测方法。使用Inception v2替换ZF网络作为Faster R-CNN的基础网络，模型精度得到显著提升；针对多牛检测场景对NMS（Non-Maximum Suppression）进行相应优化，使模型的召回率得到显著提升。通过和其他目标检测模型对比实验，本文的改进模型在精确率和召回率上均优于其他模型。

关键词: Faster R-CNN, Inception v2, NMS, 目标检测

Abstract: A cattle face detection method based on improved Faster R-CNN is proposed for multi-face detection of livestock cattle identity authentication. Inception v2 is used to replace ZF network as the basic network of Faster R-CNN, which improves the model accuracy significantly. The NMS (Non-Maximum Suppression) is optimized for the multi-cattle detection scenario, so that the recall rate of the model is significantly improved. Comparing with other detection models, the improved model is superior to others in accuracy and recall.

Key words: Faster R-CNN, Inception v2, NMS, object detection

中图分类号:

TP391.41

苟先太，黄巍，刘琪芬. 一种基于改进NMS的牛脸检测方法[J]. 计算机与现代化, doi: 10.3969/j.issn.1006-2475.2019.07.008.

GOU Xian-tai, HUANG Wei, LIU Qi-fen. A Cattle Face Detection Method Based on Improved NMS[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2019.07.008.

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一种基于改进NMS的牛脸检测方法

A Cattle Face Detection Method Based on Improved NMS

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