Class Segmentation and Object Localization with Superpixel Neighborhoods

被引：0

作者：

Fulkerson, Brian ^{[1
]}

Vedaldi, Andrea ^{[2
]}

Soatto, Stefano ^{[1
]}

机构：

[1] Univ Calif Los Angeles, Dept Comp Sci, Los Angeles, CA 90095 USA

[2] Univ Oxford, Dept Engn Sci, Oxford, England

来源：

2009 IEEE 12TH INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) | 2009年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We propose a method to identify and localize object classes in images. Instead of operating at the pixel level, we advocate the use of superpixels as the basic unit of a class segmentation or pixel localization scheme. To this end, we construct a classifier on the histogram of local features found in each superpixel. We regularize this classifier by aggregating histograms in the neighborhood of each superpixel and then refine our results further by using the classifier in a conditional random field operating on the superpixel graph. Our proposed method exceeds the previously published state-of-the-art on two challenging datasets: Graz-02 and the PASCAL VOC 2007 Segmentation Challenge.

引用

页码：670 / 677

页数：8