SPATIAL PYRAMID MINING FOR LOGO DETECTION IN NATURAL SCENES

被引：40

作者：

Kleban, Jim ^{[1
]}

Xie, Xing ^{[2
]}

Ma, Wei-Ying ^{[2
]}

机构：

[1] Univ Calif Santa Barbara, ECE Dept, Santa Barbara, CA 93106 USA

[2] Microsoft Res Asia, Beijing 100080, Peoples R China

来源：

2008 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, VOLS 1-4 | 2008年

关键词：

Data Mining; Object Detection; Mobile Search; Logo Recognition;

D O I：

10.1109/ICME.2008.4607625

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This work introduces a novel data mining scheme, spatial pyramid mining, to discover association rules at multiple resolutions in order to identify frequent spatial configurations of local features that correspond to classes of logos appearing in real world scenes. By indexing representative examples by the mined rules we can efficiently detect a variety of different lettering or design marks associated with a brand. Features in an image are marked by matching rules to representative examples selected via a weighted cosine similarity measure. Logos are localized in an image via density-based clustering of matched features. Precision vs. recall curves are presented for experiments on a dataset of web images of nearly 1,000 images containing seven popular logo types.

引用

页码：1077 / +

页数：2