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We propose an approach that parses registered images captured at ground level into architectural units for large-scale city modeling. Each parsed unit has a regularized shape, which can be used for further modeling purposes. In our approach, we first parse the environment into buildings, the ground, and the sky using a joint 2D-3D segmentation method. Then, we partition buildings into individual façades...
This paper presents an approach to extracting and using semantic layers from low altitude aerial videos for scene understanding and object tracking. The input video is captured by low flying aerial platforms and typically consists of strong parallax from non-ground-plane structures. A key aspect of our approach is the use of geo-registration of video frames to reference image databases (such as those...
A fast 3D model reconstruction methodology is desirable in many applications such as urban planning, training, and simulations. In this paper, we develop an automated algorithm for texture mapping oblique aerial images onto a 3D model generated from airborne light detection and ranging (LiDAR) data. Our proposed system consists of two steps. In the first step, we combine vanishing points and global...
Although high-resolution remote sensing (RS) images can supplement the reference map's deficiency in LADAR (Laser Radar) referenced navigation system over plain area, their different imaging modes still leave great errors' introduction into the positioning process. As positioning is commonly accomplished by matching the edges extracted as the obvious terrain characteristics, exploring automatic procedure...
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