Masafumi Uehara 
  
     
   
  
  
v image-plane 
Pi 
  
  
  
  
  
Figure 5: EEPI Figure 6: Slit image 
3 MATCHING MEASURED 3D DATA WITH DOGITAL MAP 
As mentioned in Chapter 1, it is difficult to measure 3D data of buildings because of the existence of objects, such as a 
tick growth of trees and guardrails in the real city environment. Moreover, the results of EPI analysis show that on the 
edge parts of texture alteration 3D data of buildings are densely measured meanwhile on the parts of less or no 
alteration 3D data are roughly measured. 
For the reasons given above, it has been difficult to construct the city model accurately only from measured data by EPI 
analysis. Digital map covers the 3D measured points. In the following section, we explain the matching method 
utilizing boundary information between buildings in order to match 3D data with digital map. 
3.1 Detecting boundary of buildings from depth map 
As the white points show in Figure 6, the 3D measured points appear on the parts of the vertical edge on the depth map. 
These parts are equivalent to steep texture alteration, such as boundaries between buildings, windows and doors. 
Therefore, when we make the histogram of measured points in the direction of the camera path (Z-axis), the peak of this 
histogram can be likely judged the prospective boundary of buildings (see Figure 7). At this time, we utilize the 
histogram of the measured points in the direction of the X and Z-axis with the measured points of buildings face the 
street. 
  
  
  
builds 
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Figure 6: Measured points by EPI analysis Figure 7: Histogram of measured points 
  
914 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B3. Amsterdam 2000.