基于阴影图像轮廓特征向量的三维目标检索

Raju Barskar, Gulfishan Firdose Ahmed
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引用次数: 0

摘要

随着世界上产生的新信息量的迅速增加,对结构化数据、文本和多媒体对象的集合进行高效搜索。三维对象是一种重要的多媒体数据类型,在医学、化工、CAD等领域有着广泛的应用。本文提出了一种基于阴影图像轮廓特征向量的三维目标检索方法。该方法基于我们之前提出的概念验证阴影复用方法。这项工作随后展示了如何使用和扩展计算机视觉中成熟的技术来解决形状表示和渲染中的基本问题。通常在动画、汽车和CG电影等中发现的高质量网格很难构建。为了降低整体生产成本,对现有模型进行重用或改编,进行三维对象检索。目前我们的算法对具有直边的物体可以得到很好的特征结果,但对于具有曲面的物体不能提取出很好的特征。实验结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3D object retrieval using silhouette feature vector on shady images
As the amount of new information generated in the world rapidly increases, efficient search in collections of structured data, texts and multimedia objects. 3D objects are an important type of multimedia data with many applications such as medical, chemical, CAD, etc. In this paper a great method for 3D object retrieval using silhouette feature vector on shady image. The method is based on our previously presented proof-of-concept shadow multiplexing method. This work then shows how to use and extend well-developed techniques in computer vision to address fundamental problems in shape representation and rendering. High quality meshes that are usually found in animation, automobile and CG movies etc. are difficult to build. To reduce the overall production cost, reusing or adapting from existing models 3D object retrieval is done. Currently our algorithm finds good feature results for objects having straight edges, but for objects having curve surface do not extract good features. Experimental results show the effectiveness of our Method.
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