Object detection method of few samples based on two-stage voting

doi:10.11772/j.issn.1001-9081.2014.04.1126

Journal of Computer Applications ›› 2014, Vol. 34 ›› Issue (4): 1126-1129.DOI: 10.11772/j.issn.1001-9081.2014.04.1126

• Artificial intelligence • Previous Articles Next Articles

Object detection method of few samples based on two-stage voting

XU Pei¹,ZHAO Xuezhuan²,TANG Hongqiang¹,ZHAN Weipeng¹

1. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu Sichuan 611731, China
2. Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu Sichuan 610041, China

Received:2013-10-22 Revised:2013-12-20 Online:2014-04-29 Published:2014-04-01
Contact: XU Pei

基于两阶段投票的小样本目标检测方法

徐培¹,赵雪专²,唐红强¹,占伟鹏¹

1. 电子科技大学计算机科学与工程学院,成都 611731;
2. 中国科学院成都计算机应用研究所,成都 610041

通讯作者: 徐培
作者简介:徐培(1986-),男,四川自贡人,博士研究生,主要研究方向:计算机视觉、机器学习;
赵雪专(1986-),男,河南濮阳人,博士研究生,主要研究方向:计算机视觉、机器学习;
唐红强(1987-),男,安徽安庆人,硕士研究生,主要研究方向:计算机视觉;
占伟鹏(1990-),男,江西九江人,硕士研究生,主要研究方向:计算机视觉。
基金资助:
中央基本业务经费资助项目

Abstract

Abstract:

A method of object detection with few samples based on two-stage voting was proposed to detect objects using template matching method while there are only a few samples. Firstly, the voting space was constructed off-line by using probability model through several samples. Then, a method of two-stage voting was used to detect objects in testing images. In the first stage, the components of object from testing image were detected, and the positions of components in query image were saved. In the second stage, the similarity of the object was computed integrally based on the components. According to the theory analysis and experimental results, the proposed method obtains lower computation complexity and higher precisions than previous works.

摘要：

为了在只有几个样本的情况下在待检测图像中采用模板匹配的方式定位目标，提出了一种两阶段投票的目标检测方法。首先采用概率模型通过几个样本离线构造投票空间，然后采用两阶段投票的方式在待测图像中检测目标：第一阶段在待测图像中通过投票检测目标的图像块，并记录下这些部件块在样本中所处的位置信息；第二阶段基于第一阶段所得到的图像块来投票计算样本整体的相似度，从而定位目标。理论推导和实验结果验证了所提出方法比前人的工作具有更低的时间复杂度和更高的目标检测准确率。

CLC Number:

TP391.41

XU Pei ZHAO Xuezhuan TANG Hongqiang ZHAN Weipeng. Object detection method of few samples based on two-stage voting[J]. Journal of Computer Applications, 2014, 34(4): 1126-1129.

徐培赵雪专唐红强占伟鹏. 基于两阶段投票的小样本目标检测方法[J]. 计算机应用, 2014, 34(4): 1126-1129.

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Object detection method of few samples based on two-stage voting

基于两阶段投票的小样本目标检测方法

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