PICTORIAL STRUCTURES FOR OBJECT RECOGNITION AND PART LABELING IN DRAWINGS

被引：0

作者：

Sadovnik, Amir ^{[1
]}

Chen, Tsuhan ^{[1
]}

机构：

[1] Cornell Univ, Dept Elect & Comp Engn, Ithaca, NY 14853 USA

来源：

2011 18TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2011年

关键词：

sketch recognition; pictorial structures; object detection;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Although the sketch recognition and computer vision communities attempt to solve similar problems in different domains, the sketch recognition community has not utilized many of the advancements made in computer vision algorithms. In this paper we propose using a pictorial structure model for object detection, and modify it to better perform in a drawing setting as opposed to photographs. By using this model we are able to detect a learned object in a general drawing, and correctly label its parts. We show our results on 4 categories.

引用

页数：4

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