使用二维模型的静止图像对象分类

2011 IEEE International Conference on Consumer Electronics -Berlin (ICCE-Berlin) Pub Date : 2011-09-29 DOI:10.1109/ICCE-BERLIN.2011.6031874

Raluca-Diana Petre, T. Zaharia

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引用次数: 0

摘要

本文提出了一种新的静态图像中二维物体的语义标记识别方案。该原理包括将未知的2D对象与分类的3D模型进行匹配，以便将3D对象的语义与图像相关联。我们通过使用MPEG-7和普林斯顿3D模型数据库来测试我们的新识别框架，以便标记从网络中随机选择的未知图像。实验表明，该系统的识别率可达70.4%。

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Sill image object categorization using 2D models

This paper proposes a novel recognition scheme for semantic labeling of 2D objects present in still images. The principle consists of matching unknown 2D objects with categorized 3D models in order to associate the semantics of the 3D object to the image. We tested our new recognition framework by using the MPEG-7 and Princeton 3D model databases in order to label unknown images randomly selected from the web. Experiments show that such a system can achieve recognition rate up to 70.4%.

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2011 IEEE International Conference on Consumer Electronics -Berlin (ICCE-Berlin)

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