Augmented Reality-based Guidance for Indoor Parked-car Search Using Omni-vision Techniques

Many people have the experience of getting lost in large parking lots when trying to find their parked cars. To solve this problem, an augmented reality (AR)-based automatic guidance system is proposed to help a user to find his/her parked car quickly. With multiple fisheye cameras affixed to the ceiling of the parking lot for image acquisition, the proposed system includes four major functions: user detection, user tracking, path planning, and AR-based guidance for parked-car search. To detect a user entering the parking lot, a dynamic background construction method is proposed to segment the foreground regions in a fisheye image and a dynamic thresholding method is proposed to refine the user region in the segmented regions. To track the user continuously in a large parking lot, a multiple-camera handoff method is proposed, which transfers monitoring responsibility among the cameras according to a criterion of minimizing the distance between the user’s location and the image center. Also proposed is the use of Kalman filtering for generating a smooth human track shown on the top-view parking-lot map. For path planning, a method based on the Dijsktra algorithm which yields a shortest guidance path from the entrance to the user’s parked car. To guide the user, an AR-based guidance method is proposed, which updates and overlays a guidance arrow on the screen of the user-held mobile device by utilizing the reading of the electronic compass built in the mobile device as well as the location of the next guidance path node. Good experimental results are also included to show the feasibility of the proposed system.