ON OBJECT EXTRACTION USING AIRBORNE LASER SCANNER DATA AND DIGITAL IMAGES FOR 3D MODELLING
- 1System Development and Research Center, AERO ASAHI CORPORATION, 3-1-1, Minamidai, Kawagoe, Saitama, 350-1165, Japan
- 2School of Science and Engineering, Tokyo Denki University, Ishizaka, Hatoyama, Saitama, 350-0394, Japan
- 3Division of Architectural, Civil and Environmental Engineering, Tokyo Denki University, Ishizaka, Hatoyama, Saitama, 350-0394, Japan
Keywords: LIDAR, Integration, Aerial Photogrammetry, Bundle Adjustment, Object Extraction, 3D Modelling
Abstract. Airborne laser scanners are effective at extracting the micro topography or ground surface under trees, which cannot be detected by aerial photogrammetry, and are suitable for use in many applications, such as city modelling, DTM generation, monitoring electrical power lines, and detection of forest areas. The most remarkable aspect of these systems is their ability to acquire the 3D coordinates of huge object points in real-time. There are many studies on object extraction using point clouds from airborne laser scanner data, where the shape of an object depends on the density of a point. However, this is generally used for rough shapes or fitted geometric shapes. It is difficult to reconstruct detailed object shapes without many edge points, even if high-density point clouds are obtained. On the other hand, it is possible to acquire detailed object edges from digital camera images if the digital camera is equipped with an airborne laser scanner system. The procedures investigated in this paper for improving rough object shapes using airborne laser scanner data are as follows. Firstly, camera calibration is performed to integrate point clouds and digital images by simultaneous adjustment, such as by bundle adjustment with self-calibration using distance data taken directly from airborne laser scanner data. Secondly, the rough 3D object shape is extracted from the point cloud using normal vectors. Moreover, visualization of normal vectors is used for operator interpretation. Thirdly, the rough 3D object shape is converted into the image coordinates of multiple images by a collinearity condition. The 2D coordinates of detailed image shapes are acquired using characteristic image quantities from around the rough shape. Finally, the detailed 3D shape is computed using the spatial intersection of the 2D coordinates of detailed shapes and the orientation parameters. This paper describes fundamental studies for extracting object shapes for 3D modelling using airborne laser scanner data and digital images.