In this paper we describe a system for beverage product recognition through the analysis of cooler shelf images. The extreme objects occlusion, the strong light influence and the poor quality of the images make this task a challenging one. To overcome these limitations, we rely on simple computer vision algorithms, like chamfer and color histogram matching and we introduce simple 3D modeling techniques. In our experiments, we demonstrate the effectiveness of our approach in terms of both detection accuracy and computational time.

A Computer Vision System for the Automatic Inventory of a Cooler

FIORUCCI, MARCO;Fratton, Marco;DULECHA, TINSAE GEBRECHRISTOS;PELILLO, Marcello;PRAVATO, Alberto;RONCATO, Alessandro
2017

Abstract

In this paper we describe a system for beverage product recognition through the analysis of cooler shelf images. The extreme objects occlusion, the strong light influence and the poor quality of the images make this task a challenging one. To overcome these limitations, we rely on simple computer vision algorithms, like chamfer and color histogram matching and we introduce simple 3D modeling techniques. In our experiments, we demonstrate the effectiveness of our approach in terms of both detection accuracy and computational time.
Lecture Notes in Computer Science
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10278/3689708
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