Yoichi Kunii

Building extraction and modeling in urban area by image sequence analysis

3D city modeling from airborne imagery includes mainly two parts: (1) image processing procedures and (2) 3D modeling for man-made objects such as buildings, roads and other objects. Line or feature extraction and stereo matching are usually utilized as an image processing procedures, and geometrical data acquisition for man-made objects are performed. However, there are some issues for automatic or semi-automatic man-made object modeling. These problems include uncertainty within matching, extraction of man-made objects and spatial data acquisition. In particular, spatial data acquisition of buildings are important for reliable city modeling. With this objective, this paper focuses especially on efficient and robust line matching method using optical flow, which enable an automatic building extraction since line gives important information for building extraction and satisfied results are depend on rigorous line extraction and matching. Furthermore, building extraction using morphological opening and 3D modeling for urban area are also investigated in this paper.

Line Extraction for City Modeling using Least-Median of Squares Method

3D city modeling from airborne imagery includes mainly two parts: (1) image processing procedures and (2) 3D modeling for man-made objects such as buildings, roads and other objects. Line extraction and stereo matching are usually utilized as an image processing procedures. However, there are some issues for automatic man-made object modeling. In particular, spatial data acquisition of buildings are important for reliable city modeling. In these circumstances, this paper focuses on more efficient line matching method using Least-Median of Squares (LMedS). The LMedS have ability to calculate the trifocal tensor more accurately than least squares method, and the LMedS is able to remove inaccurate matched lines during the line matching procedure. Therefore, more accurate line matching can be performed, and more efficient city modeling was realized. This paper describes more efficient line matching method using LMedS, and investigates an adaptability of this system to city modeling.