Smart Fruit Basket: Towards Multi-View Fruit Recognition

This paper discusses smart retailing solutions, self-checkout stores in particular. Since RFID tag-based product identification accounts for various limitations, the authors propose a smart basket to facilitate self-checkout mechanism for fruits and vegetables, based on multi-view image recognition and weight sensor. The system works on a multi-view model and recognizes and counts the fruit/vegetables from four camera views to handle the occlusions. The user places fruits inside the basket. Multiple cameras installed provide different views inside the basket and captures this fruit placing activity. Different views are then processed for image recognition using CNN (convolutional neural network). The authors also present a multi-view fruit recognition (MVFR) dataset to evaluate the system performance. The base of smart basket includes a weight sensor to account for weight information, the weight, and count information of fruit assist in bill generation at self-checkout station.