Enhancing Retail Product Recognition: Fine-Grained Bottle Size Classification

Abstract

In this paper, we propose two innovative approaches to tackle the key challenges in product size classification, with a specific focus on bottles. Our research is particularly interesting as we leverage the bottle cap as a reference object, which allows bottle size classification to overcome challenges in the distance between the capturing device and the retail shelf, viewing angle, and arrangement of bottles on the shelves. We showcase the usage of the reference object in explicit and implicit novel approaches and discuss the benefits and limitations of the proposed methods.