Abstract:
We live in a revolutionary world transforming everyday. This project provides real-time video analytics that can help retail stores to increase their point of sale and promotes a better customer experience. We aim to develop a “Web-Based Real-Time Crowd Analysis in Retail” which has a proper dashboard with all real-time analytics in graphical representation and a summary of current analytics happening at that time. Our dashboard can provide people count analytics including their count and peak hours estimate. Gender classificationbased analytics shows a total number of males and females. This will also show the number of shoplifters detected and generates an alert if any shoplifting or suspicious activity detects. Overall analytics include the total number of people entering or exiting count. Such information allows for enhanced customer experience, optimized store performance, reduced operational costs, and ultimately higher profitability. Chapter 1 mention the brief introduction, background of the “ Web-Based Real-Time Analysis For Retail”. In Chapter 2 Literature review we will discuss the comparative study and similar work. Chapter 3 presents the requirement specifications while Chapter 4 details the system design. System implementation is discussed in Chapter 5 while Chapter 6 presents the results of the experimental evaluations. Finally, we conclude the report in Chapter 7.
