The use‑case featured Lolli and Pops, Inc., a gourmet candy retailer in the United States.
It uses computer vision with facial recognition to identify frequent buyers as they enter the store.
Labellerr provides the data‑annotation service (https://zcu.io/NxQb) to ensure accurate face‑tagging in real‑time.
Instant #LoyaltyRewards always draw customers more frequently to the store.
The MERL shopping dataset contains 106 videos each approx. 2 min duration and provides fine‑grained hand‑shelf interaction labels for retail behavior analysis.