Description
Grab is a sensor processing system for cashier-free shopping. Grab needs to accurately identify and track customers, and associate each shopper with items he or she retrieves from shelves. To do this, it uses a keypoint-based pose tracker as a building block for identification and tracking, develops robust feature-based face trackers, and algorithms for associating and tracking arm movements. It also uses a probabilistic framework to fuse readings from camera, weight and RFID sensors in order to accurately assess which shopper picks up which item.
Papers Using This Method
Revealing Hidden Mechanisms of Cross-Country Content Moderation with Natural Language Processing2025-03-07Spatial Entity Resolution between Restaurant Locations and Transportation Destinations in Southeast Asia2024-01-16Conditional Expectation based Value Decomposition for Scalable On-Demand Ride Pooling2021-12-01Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload2021-03-23Understanding the Dynamics of Drivers' Locations for Passengers Pickup Performance: A Case Study2020-09-09Grab: Fast and Accurate Sensor Processing for Cashier-Free Shopping2020-01-04