Object Detection Using Hough Transform and Conditional Random Field Model

被引：0

作者：

Du, Benhan ^{[1
]}

Yang, Zhen ^{[1
]}

Xiong, Huilin ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Inst Image Proc & Pattern Recognit, Dept Automat, Shanghai, Peoples R China

来源：

2013 3RD INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT) | 2013年

基金：

美国国家科学基金会;

关键词：

object detection; Hough transform; Conditional Random Field; conditional probabilistic model;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Hough transform provides a different and effective way for object detection. This approach has attracted much attention since the implicit shape model (ISM) was proposed. Inspired by the Implicit Shape Model and Conditional Random Field (CRF), we present in this paper a conditional probabilistic model to formulate the relationship between the voting elements and the hypotheses in the Hough transform. Based on this model, an efficient object detection scheme is proposed and experimental results demonstrate the effectiveness of the proposed scheme.

引用

页码：512 / 516

页数：5

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