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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Fruh, C. Zakhor, A. |
| Copyright Year | 2001 |
| Description | Author affiliation: Video & Image Process. Lab., California Univ., Berkeley, CA, USA (Fruh, C.; Zakhor, A.) |
| Abstract | In this paper we describe techniques for 3D textured model construction of urban areas using acquisition devices such as intensity cameras, as well as 2D laser scanner. Our experimental set up consists of a truck equipped with one camera and two fast, inexpensive 2D laser scanner, traveling on city streets under normal traffic conditions. The horizontal laser scans are used to determine the approximate component of motion along the movement of the acquisition vehicle. The vertical scanner is used to build 3D models of the facade of the buildings. To improve the accuracy of localization of the truck and hence our resulting 3D models of the city, two different methods are developed and compared: the first method employs a correlation technique and the second method is based on Markov Monte Carlo localization. Both techniques use digital road maps and aerial photographs in conjunction with laser scans. A fairly accurate textured, 3D model of downtown area has been acquired in a matter of few minutes, limited only by traffic conditions during the data acquisition phase. |
| Sponsorship | IEEE Comput. Soc. Tech. Committee on Pattern Analysis & Machine Intelligence |
| File Size | 1260332 |
| File Format | |
| ISBN | 0769512720 |
| ISSN | 10636919 |
| DOI | 10.1109/CVPR.2001.990921 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2001-12-08 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Cities and towns Laser modes Cameras Data acquisition Traffic control Vehicles Roads Remote monitoring Global Positioning System Image processing |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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