Part 3/17:
One of the foundational use cases discussed is people counting, which, although simple in concept, remains profoundly useful. Initially relying on complex traditional image processing algorithms in the early 2000s, accuracy was often hampered by environmental factors like lighting and shadows. Post-2012, deep learning models have dramatically improved precision, even in complex scenes.
In retail settings, this technology enables insights such as foot traffic analysis, footfall-to-sales conversions, and customer movement patterns. Outside retail, crowd management and public safety have benefited immensely, especially during the COVID-19 pandemic, where occupancy management became critical for safety compliance.