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3D models of large-scale scenes available on the Internet today are largely manually created. Thus it takes a long time to create them for cities and update them as those cities that are already modeled continue to change. Multiple parallel-perspective mosaics can be generated from video automatically and more efficiently and can be used to reconstruct 3D scenes faster. A lot of video currently exists...
This paper presents a framework to analyze a large amount of video data and extract high-level structural information - planar structures and motion information - in typical urban scenes, which may be used in video coding or object recognition. The method consists of two phases. In the first phase, multiple parallel-perspective (pushbroom) mosaics are generated from the video data. In the second phase,...
In this paper, a unified, segmentation-based approach is proposed to deal with both stereo reconstruction and moving objects detection problems using multiple stereo mosaics. Each set of parallel-perspective (pushbroom) stereo mosaics is generated from a video sequence captured by a single video camera. First a color-segmentation approach is used to extract the so-called natural matching primitives...
We propose a content-based 3D mosaic representation for long video sequences of 3D and dynamic scenes captured by a camera on a mobile platform. The motion of the camera has a dominant direction of motion (as on an airplane or ground vehicle), but 6 degrees-of-freedom (DOF) motion is allowed. In the first step, a pair of generalized parallel-perspective (pushbroom) stereo mosaics is generated that...
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