Abstract
A majority of foodborne illnesses result from inappropriate food handling practices. One proven practice to reduce pathogens is to perform effective hand-hygiene before all stages of food handling. In this paper, we design a multi-camera system that uses video analytics to recognize hand-hygiene actions, with the goal of improving hand-hygiene effectiveness. Our proposed two-stage system processes untrimmed video from both egocentric and third-person cameras. In the first stage, a low-cost coarse classifier efficiently localizes the hand-hygiene period; in the second stage, more complex refinement classifiers recognize seven specific actions within the hand-hygiene period. We demonstrate that our two-stage system has significantly lower computational requirements without a loss of recognition accuracy. Specifically, the computationally complex refinement classifiers process less than 68% of the untrimmed videos, and we anticipate further computational gains in videos that contain a larger fraction of non-hygiene actions. Our results demonstrate that a carefully designed video action recognition system can play an important role in improving hand hygiene for food safety.
Highlights
We use multi-camera video analytic methods to design a system that recognizes hand-hygiene actions for food safety
In recent years, where the burden of foodborne illnesses is increasing, evidence indicates that the majority of food contamination is caused by inappropriate food manufacturing practices, involving workers with poor food handling skills [1]
We consider video monitoring combined with video-analytic methods for food handling evaluation to be a fast and cost-efficient way to do self-assessment for food growers, processors, and/or handlers
Summary
We use multi-camera video analytic methods to design a system that recognizes hand-hygiene actions for food safety. Food safety is a discipline that describes scientific methods to prevent contamination and foodborne illness at different stages of food production. The stages include, but are not limited to, food handling, food storage, equipment cleaning, and staff hygiene. In recent years, where the burden of foodborne illnesses is increasing, evidence indicates that the majority of food contamination is caused by inappropriate food manufacturing practices, involving workers with poor food handling skills [1]. We consider video monitoring combined with video-analytic methods for food handling evaluation to be a fast and cost-efficient way to do self-assessment for food growers, processors, and/or handlers. There are many steps to achieve good manufacturing practices (GMPs)
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