Customer Analytics using Surveillance Video

Earnest Paul Ijjina, Aniruddha Srinivas Joshi, Goutham Kanahasabai, Keerthi Priyanka P
3/1/2025
cs.CYcs.CVcs.LG

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Abstract

The analysis of sales information, is a vital step in designing an effective marketing strategy. This work proposes a novel approach to analyse the shopping behaviour of customers to identify their purchase patterns. An extended version of the Multi-Cluster Overlapping k-Means Extension (MCOKE) algorithm with weighted k-Means algorithm is utilized to map customers to the garments of interest. The age & gender traits of the customer; the time spent and the expressions exhibited while selecting garments for purchase, are utilized to associate a customer or a group of customers to a garments they are interested in. Such study on the customer base of a retail business, may help in inferring the products of interest of their consumers, and enable them in developing effective business strategies, thus ensuring customer satisfaction, loyalty, increased sales and profits.

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Cite this paper

@article{ijjina2025customer,
  title  = {Customer Analytics using Surveillance Video},
  author = {Earnest Paul Ijjina and Aniruddha Srinivas Joshi and Goutham Kanahasabai and Keerthi Priyanka P},
  year   = {2025},
  eprint = {2503.00452},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2503.00452v1}
}

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