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Video analytics solution for tracking customer locations in retail shopping malls

Published: 21 August 2011 Publication History

Abstract

Due to increased adoption of digital inclusion in various businesses, location based services are gaining importance to provide value-added services for their customers. In this work, we present a computer vision based system for tracking customer locations by recognizing individual shopping carts inside shopping malls in order to facilitate location based services. We provide an efficient approach for cart recognition that consists of two stages: cart detection and then cart recognition. A binary pattern is placed between two pre-defined color markers and attached to each cart for recognition. The system takes live video feed as input from the cameras mounted on the aisles of the shopping mall and processes frames in real-time. In the cart detection stage, color segmentation, feature extraction and classification are used for detection of binary pattern along with color markers. In recognition stage, segmented binary strip is processed using spatial image processing techniques to decode the cart identification number.

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Cited By

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  • (2023)Challenges in Adoption of Business Analytics by Small RetailersInternational Journal of E-Adoption10.4018/IJEA.31653915:2(1-14)Online publication date: 13-Jan-2023
  • (2020)Influence of technological advances and change in marketing strategies using analytics in retail industryInternational Journal of System Assurance Engineering and Management10.1007/s13198-020-01023-511:5(953-961)Online publication date: 13-Aug-2020
  • (2017)Design considerations for multi-stakeholder display analyticsProceedings of the 6th ACM International Symposium on Pervasive Displays10.1145/3078810.3078830(1-10)Online publication date: 7-Jun-2017
  • Show More Cited By

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cover image ACM Conferences
KDD '11: Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
August 2011
1446 pages
ISBN:9781450308137
DOI:10.1145/2020408
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

Publication History

Published: 21 August 2011

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Author Tags

  1. classification
  2. color segmentation
  3. haar-like features
  4. shopping cart detection

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Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Cited By

View all
  • (2023)Challenges in Adoption of Business Analytics by Small RetailersInternational Journal of E-Adoption10.4018/IJEA.31653915:2(1-14)Online publication date: 13-Jan-2023
  • (2020)Influence of technological advances and change in marketing strategies using analytics in retail industryInternational Journal of System Assurance Engineering and Management10.1007/s13198-020-01023-511:5(953-961)Online publication date: 13-Aug-2020
  • (2017)Design considerations for multi-stakeholder display analyticsProceedings of the 6th ACM International Symposium on Pervasive Displays10.1145/3078810.3078830(1-10)Online publication date: 7-Jun-2017
  • (2017)Challenges and Opportunities in Designing Smart SpacesInternet of Everything10.1007/978-981-10-5861-5_6(131-152)Online publication date: 17-Oct-2017
  • (2013)Understanding customer malling behavior in an urban shopping mall using smartphonesProceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication10.1145/2494091.2497344(901-910)Online publication date: 8-Sep-2013
  • (2013)Explaining the product range effect in purchase data2013 IEEE International Conference on Big Data10.1109/BigData.2013.6691634(648-656)Online publication date: Oct-2013

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