Prototyping Indoor Maps with VLMs: From Photos to Positions

Over a weekend, the author prototyped an indoor localization system using a single photo and cutting-edge Vision-Language Models (VLMs). By annotating a mall map, identifying visible shops in the photo, and leveraging the VLM's image recognition capabilities, the system successfully matched the photo's location to the map. While some ambiguity remains, the results are surprisingly accurate, showcasing the potential of VLMs for indoor localization. This opens exciting avenues for future AR applications and robotics, while also highlighting potential environmental concerns.