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Proceedings Paper

Real-time video analysis for retail stores
Author(s): Ehtesham Hassan; Avinash Kumar Maurya
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Paper Abstract

With the advancement in video processing technologies, we can capture subtle human responses in a retail store environment which play decisive role in the store management. In this paper, we present a novel surveillance video based analytic system for retail stores targeting localized and global traffic estimate. Development of an intelligent system for human traffic estimation in real-life poses a challenging problem because of the variation and noise involved. In this direction, we begin with a novel human tracking system by an intelligent combination of motion based and image level object detection. We demonstrate the initial evaluation of this approach on available standard dataset yielding promising result. Exact traffic estimate in a retail store require correct separation of customers from service providers. We present a role based human classification framework using Gaussian mixture model for this task. A novel feature descriptor named graded colour histogram is defined for object representation. Using, our role based human classification and tracking system, we have defined a novel computationally efficient framework for two types of analytics generation i.e., region specific people count and dwell-time estimation. This system has been extensively evaluated and tested on four hours of real-life video captured from a retail store.

Paper Details

Date Published: 4 March 2015
PDF: 10 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94432B (4 March 2015); doi: 10.1117/12.2179969
Show Author Affiliations
Ehtesham Hassan, Tata Consultancy Services, Ltd. (India)
Avinash Kumar Maurya, Tata Consultancy Services, Ltd. (India)

Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)

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