A connectionist approach to multiple-view based 3-D object recognition

Wei-Chung Lin, Fong-Yuan Liao, E. Tsao, Theresa Lingutla
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Abstract

The authors propose a hierarchical approach to solving the surface and the vertex correspondence problems in multiple-view based 3-D object recognition systems. The proposed scheme is a coarse-to-fine search process, and a Hopfield network is employed at each stage. Compared with the conventional object matching schemes, the proposed technique provides a more general and compact formulation of the problem and a solution more suitable for parallel implementation. At the coarse search stage, the surface matching rates between the input image and each object model in the database are computed through a Hopfield network and used to select the candidates for further consideration. At the fine search stage, the object models selected from the previous stage are fed into another Hopfield network for vertex matching. The object model that has the best surface and vertex correspondences with the input image is finally singled out as the best matched model. Results of experiments using both line drawings and real range images to corroborate the proposed theory are also reported.<>
一种基于多视图的三维物体识别连接方法
提出了一种分层方法来解决基于多视图的三维物体识别系统中曲面与顶点的对应问题。该方案是一个从粗到精的搜索过程,每个阶段都采用Hopfield网络。与传统的目标匹配方案相比,该技术提供了更通用、更紧凑的问题表述和更适合并行实现的解决方案。在粗搜索阶段,通过Hopfield网络计算输入图像与数据库中每个目标模型之间的表面匹配率,并用于选择候选对象进行进一步考虑。在精细搜索阶段,将前一阶段选择的目标模型送入另一个Hopfield网络进行顶点匹配。最后选出与输入图像表面和顶点对应度最好的目标模型作为最佳匹配模型。本文还报道了用直线图和实际距离图像验证该理论的实验结果。
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