Robust Object Detection with Interleaved Categorization and Segmentation

被引：0
|
作者：
Bastian Leibe
Aleš Leonardis
Bernt Schiele
机构：
[1] ETH Zurich,Computer Vision Laboratory
[2] University of Ljubljana,Faculty of Computer and Information Science
[3] TU Darmstadt,Department of Computer Science
来源：
International Journal of Computer Vision | 2008年 / 77卷
关键词：
Object categorization; Object detection; Segmentation; Clustering; Hough transform; Hypothesis selection; MDL;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper presents a novel method for detecting and localizing objects of a visual category in cluttered real-world scenes. Our approach considers object categorization and figure-ground segmentation as two interleaved processes that closely collaborate towards a common goal. As shown in our work, the tight coupling between those two processes allows them to benefit from each other and improve the combined performance.
引用
收藏
页码：259 / 289
页数：30
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