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AUTOMATIC STEREO MATCHING USING OPTICAL FLOW FOR 3D OBJECT MODELING
Yoichi KUNIT , Hirofumi CHIKATSU
Tokyo Denki University, Japan
Department of Civil Engineering
99smg08@g.dendai.ac.j
**
chikatsu(g)g.dendai.ac.]p
Working Group IC V/III
KEY WORDS: Optical Flow, 3D Object Modeling, Stereo Matching, Coplanarity Condition, Line Tracking,
Sequential Images.
ABSTRACT
In order to acquire 3D spatial data for objects using stereo image, stereo matching such as SSDA, area based matching
and so on have been proposed. However, there are some issues for efficient 3D object modeling. In particular, efficient
line matching for reconstruction of the objects such as buildings is needed to be resolved. With this objective, this paper
investigates automatic stereo matching method using optical flow estimation. Furthermore, this paper investigates a 3D
spatial data acquisition method using coplanarity condition, and shows 3D modeling of a building which was performed
automatically.
1 INTRODUCTION
Recently, efficient spatial data acquisition and visualization have been received more attention from the view point of
3D-GIS, city modeling, and so on. Generally, 3D spatial data is acquired by stereo matching, and there are many stereo
matching methods, e.g. SSDA, area based matching. However, automated segmentation of feature areas or extraction of
feature lines of objects are still issues which are needed to be resolved for efficient modeling. With this objective, this
paper investigates an automatic stereo matching method using optical flow. The optical flow is estimated using
sequential images for objects, and the optical flow has ability for line tracking. The line tracking is performed
automatically in the sequential images from the first frame to the last frame. Then, this paper shows that the stereo
matching can be performed automatically, and the feature lines for objects can be acquired simultaneously.
Furthermore, 3D spatial data acquisition method using coplanarity condition is investigated as follows: Firstly relative
ground coordinates are calculated by the relative orientation using coplanarity condition. Secondly, the relative ground
coordinates are transformed to absolute ground coordinates. Finally, the absolute ground coordinates were set as
approximate values for the bundle adjustment, and 3D coordinates of the each point on the object are calculated.
Therefore, 3D spatial data can be acquired efficiently, and shows that 3D modeling of a building is performed
automatically in this paper.
2 AUTOMATIC 3D OBJECT MODELING METHOD
2. Automatic Stereo Matching
Stereo matching was performed automatically using optical flow in this paper. The detail procedures of the automatic
stereo matching method are as follows.
2.1.1 Line Extraction: The line extraction was performed by Canny operator (CANNY, J., 1986.) with 2 threshold
values relative to 2 components which called the height and reliability of edge in this paper (YOKOYAMA, H. etal,
1998.). The height of edge is a variation of the gray level periphery at the point, and the reliability is an index for
representing influence of noise. Threshold value of height was set at 10, and reliability was set at 0.1 in this paper. In
order to perform line tracking, each both ends for the line was connected by straight line. Figure 1 shows original image
of the house model and figure 2(a) shows filtering image land (b) shows straight line image.
International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B5. Amsterdam 2000. 459