Augmented reality in e-commerce with markerless tracking

• Published in: 2010 2nd IEEE International Conference on Information Management and Engineering pp. 609 - 613
• Main Authors: Xinyu Li, Dongyi Chen
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.04.2010
• Subjects: Augmented reality; Automation; Chaos; Consumer electronics; E-commerce; Electronic commerce; Feature extraction; feature matching; Industrial training; Internet; Layout; neural network; Neural networks
• ISBN: 9781424452637; 1424452635
• DOI: 10.1109/ICIME.2010.5478308

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.