Bill Board Data Analysis

This research delves into an in-depth examination of billboard advertisements, with a particular emphasis on quantifying and analyzing the depiction of human figures. The project's core objective is to explore how human imagery is utilized in billboard advertising and what this reveals about marketing trends, demographic targeting, and visual strategies in public spaces.

Employing sophisticated image processing techniques, the study systematically identifies and counts human representations in a large dataset of billboard images gathered from diverse geographic locations. This approach is enhanced by the use of advanced machine learning algorithms, trained to discern human figures with high accuracy, even in complex visual backgrounds.

KEYWORDS: deep learning, Yolov3, human count, bill board analysis, image processing.