In this paper we study the beverage package recognition problem for mobile applications. Unlike products such as books and CDs that are primarily packaged in rigid forms, the beverage labels may be attached on various forms including cans and bottles. Therefore, query images captured by users may have a wide range or variations in appearance. Furthermore, similar visual patterns may appear on distinct beverage packages that belong to the same series. To address these challenges, we propose a fast, hierarchical approach that can be used to effectively recognize a beverage package in real-time. A weighting scheme is introduced to enhance the recognition accuracy rate when the query beverage is among flavor varieties in a series. We examine the development of a practical system that can achieve a fairly good recognition performance (93% accuracy rate using an evaluation set of 120 images) in real-time.