Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 537-544, 2016
https://doi.org/10.5194/isprs-archives-XLI-B1-537-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
03 Jun 2016
A METHOD OF GENERATING PANORAMIC STREET STRIP IMAGE MAP WITH MOBILE MAPPING SYSTEM
Chen Tianen, Kohei Yamamoto, and Kikuo Tachibana PASCO CORP. R&D CENTER, 2-8-10 Higashiyama Meguro-Ku, Tokyo 153-0043, Japan
Keywords: Mobile Mapping System, Omni-Directional Camera, Laser Point Cloud, Street-Side Map, Image Stitching Abstract. This paper explores a method of generating panoramic street strip image map which is called as “Pano-Street” here and contains both sides, ground surface and overhead part of a street with a sequence of 360° panoramic images captured with Point Grey’s Ladybug3 mounted on the top of Mitsubishi MMS-X 220 at 2m intervals along the streets in urban environment. On-board GPS/IMU, speedometer and post sequence image analysis technology such as bundle adjustment provided much more accuracy level position and attitude data for these panoramic images, and laser data. The principle for generating panoramic street strip image map is similar to that of the traditional aero ortho-images. A special 3D DEM(3D-Mesh called here) was firstly generated with laser data, the depth map generated from dense image matching with the sequence of 360° panoramic images, or the existing GIS spatial data along the MMS trajectory, then all 360° panoramic images were projected and stitched on the 3D-Mesh with the position and attitude data. This makes it possible to make large scale panoramic street strip image maps for most types of cities, and provides another kind of street view way to view the 360° scene along the street by avoiding the switch of image bubbles like Google Street View and Bing Maps Streetside.
Conference paper (PDF, 1132 KB)


Citation: Tianen, C., Yamamoto, K., and Tachibana, K.: A METHOD OF GENERATING PANORAMIC STREET STRIP IMAGE MAP WITH MOBILE MAPPING SYSTEM, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 537-544, https://doi.org/10.5194/isprs-archives-XLI-B1-537-2016, 2016.

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