Work Surface Arrangement Optimization Driven by Human Activity

In this paper, we aim at guiding people to accomplish a personalized task, work surface organizing, in mixed reality environment, which can also be applied to intelligent robots. Through the cameras mounted in a MR device, e.g., Hololens, we firstly capture a person's daily activities in real scene when he uses the work surface. From such activities, we model the individual behavior habits and apply them to optimize the arrangement of the work surface. A cost function is defined for the optimization, considering general arrangement rules and human habitual behavior. The optimized arrangement is suggested to the user by augmenting the virtual arrangement on the real scene. To evaluate the effectiveness of our approach, we conducted experiments on a variety of scenes.