Collaborative vision network for personalized office ergonomics

This paper proposes a collaborative vision network that leverages a personal webcam and cameras of the workplace to provide feedback relating to an office-worker's adherence to ergonomic guidelines. This can lead to increased well-being for the individual and better productivity in their work. The proposed system is evaluated with a recorded multi-camera dataset from a regular office environment. First, analysis results on various ergonomic issues are presented based on personal webcams of the two workers. Second, both personal and ambient cameras are used through sensor fusion to infer the mobility state of one of the workers. Results for various fusion approaches are shown and their impact on vision network design is briefly discussed.