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What is it about?

When searching for a dynamic target in an unknown real world scene, search efficiency is greatly reduced if users lack information about the spatial structure of the scene. Most target search studies, especially in robotics, focus on determining either the shortest path when the target’s position is known, or a strategy to find the target as quickly as possible when the target’s position is unknown. However, the target’s position is often known intermittently in the real world, e.g., in the case of using surveillance cameras. Our goal is to help user find a dynamic target efficiently in the real world when the target’s position is intermittently known. In order to achieve this purpose, we have designed an AR guidance assistance system to provide optimal current directional guidance to users, based on searching a prediction graph. We assume that a certain number of depth cameras are fixed in a real scene to obtain dynamic target’s position. The system automatically analyzes all possible meetings between the user and the target, and generates optimal directional guidance to help the user catch up with the target. A user study was used to evaluate our method, and its results showed that compared to free search and a top-view method, our method significantly improves target search efficiency.

Featured Image

Photo by Mick Haupt on Unsplash

Photo by Mick Haupt on Unsplash

Why is it important?

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Perspectives