Snap n' shop: Visual search-based mobile shopping made a breeze by machine and crowd intelligence

Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015) Pub Date : 2015-02-01 DOI:10.1109/ICOSC.2015.7050803

Quanzeng You, Jianbo Yuan, Jiaqi Wang, Philip J. Guo, Jiebo Luo

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引用次数: 4

Abstract

The increasing popularity of smartphones has significantly changed the way we live. Today's powerful mobile systems provide us with all kinds of convenient services. Thanks to the wide variety of available apps, it has never been so easy for people to shop, to navigate, and to communicate with others. However, for some tasks we can further improve the user experience by employing newly developed algorithms. In this work, we try to improve visual search based mobile shopping experience by using machine and crowd intelligence. In particular, our system enables precise object selection, which would lead to more accurate visual search results. We also use crowdsourcing to further extend the system's prowess. We conduct experiments on user interface design and retrieval performance, which validate the effectiveness and ease of use of the proposed system. Meanwhile, components in the system are quite modular, allowing the flexibility of adding or improving different modules of the whole system.

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Snap n' shop:基于视觉搜索的移动购物通过机器和人群智能变得轻而易举

智能手机的日益普及极大地改变了我们的生活方式。当今强大的移动系统为我们提供了各种便捷的服务。由于应用程序种类繁多，人们购物、导航和与他人交流从未如此容易。然而，对于某些任务，我们可以通过采用新开发的算法进一步改善用户体验。在这项工作中，我们试图通过使用机器和人群智能来改善基于视觉搜索的移动购物体验。特别是，我们的系统支持精确的对象选择，这将导致更准确的视觉搜索结果。我们还使用众包来进一步扩展系统的威力。在用户界面设计和检索性能方面进行了实验，验证了系统的有效性和易用性。同时，系统中的组件是模块化的，可以灵活地增加或改进整个系统的不同模块。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015)

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