Smart Shopping Assistant: A Multimedia and Social Media Augmented System with Mobile Devices to Enhance Customers' Experience and Interaction

Multimedia, social media content, and interaction are common means to attract customers in shopping. However these features are not always fully available for customers when they go shopping in physical shopping centers. The authors propose Smart Shopping Assistant, a multimedia and social media augmented system on mobile devices to enhance users’ experience and interaction in shopping. Smart Shopping turns a regular mobile device into a special prism so that a customer can enjoy multimedia, get useful social media related to a product, give feedbacks or make actions on a product during shopping. The system is specified as a flexible framework to take advantages of different visual descriptors and web information extraction modules. Experimental results show that Smart Shopping can process and provide augmented data in a realtime-manner. Smart Shopping can be used to attract more customers and to build an online social community of customers to share their interests in shopping.

[1]  Fidel Cacheda,et al.  Finding and Extracting Data Records from Web Pages , 2007, EUC.

[2]  C. Herstatt,et al.  From Electronic to Mobile Commerce: Opportunities Through Technology Convergence for Business Services , 2006 .

[3]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[4]  Borko Furht,et al.  Handbook of Augmented Reality , 2011 .

[5]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[6]  Michael Werman,et al.  The Quadratic-Chi Histogram Distance Family , 2010, ECCV.

[7]  Adrian Kapczyński,et al.  Internet - Technical Development and Applications , 2009 .

[8]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Scott R. Klemmer,et al.  Programming by a sample: rapidly creating web applications with d.mix , 2007, UIST.

[10]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[11]  Fidel Cacheda,et al.  Finding and Extracting Data Records from Web Pages , 2010, J. Signal Process. Syst..

[12]  Tung Bui,et al.  Harnessing the Influence of Social Proof in Online Shopping: The Effect of Electronic Word of Mouth on Sales of Digital Microproducts , 2011, Int. J. Electron. Commer..

[13]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[14]  P. Mell,et al.  The NIST Definition of Cloud Computing , 2011 .

[15]  María-del-Carmen Alarcón-del-Amo,et al.  Social Networking Sites as Business Tool: A Study of User Behavior , 2013, Business Process Management.

[16]  Amanda Spink,et al.  Trends in Searching for Commerce Related Information on Web Search Engines , 2008 .

[17]  Carlo Tomasi,et al.  Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[18]  R. Tiwari,et al.  The Mobile Commerce Prospects. A Strategic Analysis of Opportunities in the Banking Sector , 2007 .

[19]  Richard Szeliski,et al.  Computer Vision - Algorithms and Applications , 2011, Texts in Computer Science.

[20]  Nina S. T. Hirata,et al.  Fast QR Code Detection in Arbitrarily Acquired Images , 2011, 2011 24th SIBGRAPI Conference on Graphics, Patterns and Images.

[21]  R. Cialdini.  Influence: The Psychology of Persuasion , 1993 .

[22]  Hye-Young Paik,et al.  Data integration in mashups , 2009, SGMD.

[23]  Amanda Spink,et al.  Web Search: Public Searching of the Web , 2011, Information Science and Knowledge Management.

[24]  Ángel Viña,et al.  Semi-Automatic Wrapper Generation for Commercial Web Sources , 2002, Engineering Information Systems in the Internet Context.

[25]  Valter Crescenzi,et al.  RoadRunner: Towards Automatic Data Extraction from Large Web Sites , 2001, VLDB.

[26]  J. P. Lewis.  Fast Normalized Cross-Correlation , 2010 .

[27]  Hiroshi Hanaizumi,et al.  Barcode readers using the camera device in mobile phones , 2004, 2004 International Conference on Cyberworlds.

[28]  R. Cialdini.  Influence: Science and Practice , 1984 .

[29]  Huoy Min Khoo,et al.  The Evolution of e-Commerce Research: A Stakeholder Perspective , 2005 .

[30]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .