Automatic Guidance for Indoor Car Parking Using Augmented-reality and Omni-vision Techniques

• Main Authors: Chen, Jair, 陳頡
• Other Authors: Tsai, Wen-Hsiang
• Format: Others
• Language: en_US
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/13395780228921601943

碩士 === 國立交通大學 === 多媒體工程研究所 === 102 === When driving a car into a large parking lot, a driver always needs to find a parking space and sometimes has to stand in line for a long time before a parking space becomes available. After entering the parking lot, it might even be necessary to drive around the entire parking lot more than once before an empty space can be found out. To solve such a parking-space finding problem, an augmented reality (AR)-based guidance system is proposed in this study to help a driver to save parking time, which has the functions of both finding empty parking spaces automatically and displaying a planned path to guide the driver to an empty space on a user’s mobile-device screen in an AR way. The proposed system includes four major components, including car detection and tracking, parking-space detection, path planning, and AR-based guidance for car parking. In order to detect and track a car driven in the parking lot, a car localization method by using 3D bounding boxes is proposed to find the current position of the car. Furthermore, a car detection method by using a gingko-shaped prediction area is proposed to refine the car localization result. Finally, the concept of virtual fence is used to find a start point for the car detection process. The idea of tracking continuity is also applied to get the best tracking accuracy. And the trajectory of the car is drawn onto the environment map. In such a way, the driver is able to know where he/she is in the parking lot by looking at the map. In order to find empty parking spaces in the parking lot, a dynamic environment learning technique and a parking-space detection method based on the use of 3D bounding boxes are proposed, by which the system can find out the positions of all empty parking spaces among which the driver can select one as the destination for car parking. Also proposed is a new method for path planning which is based on the Dijsktra algorithm and yields a shortest path from the current location of the car to the selected empty parking space. In order to guide the driver, an integral method for generating panorama images and perspective-view images from fisheye images is proposed, by which the driver can get an AR-based guidance image with the planned navigation path drawn on it. By following the augmented navigation path in the image which is displayed on the mobile-device screen, the driver can finally get to the empty parking-space that he/she chooses. Good experimental results showing the feasibility of the proposed system and methods are also included.