Augmented reality in e-commerce with markerless tracking
Augmented reality in e-commerce with markerless tracking
复制标题
电子商务中的增强现实与无标记跟踪
DOI：
10.1109/icime.2010.5478308
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Dongyi Chen
中科院分区：
文献类型：
--
作者：
Xinyu Li;Dongyi Chen
目前的电子商务技术不能向买家提供足够的个人信息。增强现实(AR)技术可以将产品的虚拟信息叠加到现实世界中，从而提高电子商务的性能。但传统的基于标记的跟踪技术阻碍了AR技术在商业上的应用。提出了一种基于暂态混沌神经网络的图像序列特征点匹配方法。通过这种方法，一种新的具有图像特征的无标记视觉跟踪技术可以应用于AR电子商务应用中。基于特征点的神经网络图像匹配方法近年来引起了人们的广泛关注。首先从图像中提取旋转和尺度不变的特征，然后利用暂态混沌神经网络进行全局特征匹配，并进行跟踪的初始化阶段。实验结果证明了该方法的有效性和高效性。
Current E-commerce technologies cannot provide enough individual information to buyers. Augmented Reality (AR) technology might improve the performance of E-commerce by overlaying virtual information of products on the real world. But usual tracking technology based on markers is impeding the application of AR technology in business. This paper proposes an approach to feature point correspondence of image sequence based on transient chaotic neural networks. Through this approach a new markerless visual tracking technology with image feature can be used in AR E-commerce applications. Feature point based neural network image matching method has attracted considerable attention in recent years. Rotation and scale invariant features are extracted from images firstly, and then transient chaotic neural network is used to perform global feature matching and perform the initialization phase of the tracking. Experimental results demonstrate the efficiency and the effectiveness of the proposed method.