We consider the task of localizing shopping carts in a retail store from egocentric images. Addressing this task allows to infer information on the behavior of the customers to understand how they move in the store and what they pay more attention to. To study the problem, we propose a large dataset of images collected in a real retail store
EgoCart: a Benchmark Dataset for Large-Scale Indoor Image-Based Localization in Retail Stores
Spera, Emiliano;Furnari, Antonino;Battiato, Sebastiano;Farinella, Giovanni Maria
2021-01-01
Abstract
We consider the task of localizing shopping carts in a retail store from egocentric images. Addressing this task allows to infer information on the behavior of the customers to understand how they move in the store and what they pay more attention to. To study the problem, we propose a large dataset of images collected in a real retail storeFile in questo prodotto:
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