An Event-Based Hierarchical Method for Customer Activity Recognition in Retail Stores

Customer Activity (CA) provides valuable information for marketing. CA is a collective name of customer information from on-the-spot observation in retail environments. Existing methods of Customer Activity Recognition (CAR) recognize CA by specialized end-to-end (e2e) models. Consequently, when marketing requires changing recognition targets, specialized e2e models are not reconfigurable to fit different marketing demands unless rebuilding the models entirely. Besides, redundant computation in the existing CAR system leads to low efficiency. Also, the low maintainability of the CAR system results in lots of modifications when updating methods in the system. In this research, we decompose behaviors into several primitive units called “event”. We propose an event-based CAR method to achieve reconfigurability and design a hierarchy to solve issues about redundancy and maintainability. The evaluation results show that our proposed method can adapt and perform better than existing methods, which fits different marketing demands.