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—In this paper, we propose a robust framework for building extraction in visible band images. We first get an initial classification of the pixels based on an unsupervised presegmen-tation. Then, we develop a novel conditional random field (CRF) formulation to achieve accurate rooftops extraction, which incorporates pixel-level information and segment-level(More)
Decomposition and segmentation of the objects represented by point cloud data become increasingly important for purposes like shape analysis and object recognition. In this paper, we propose a perception based approach to segment point cloud into distinct parts, and the decomposition is made possible of spatially close but geodetically distant parts.(More)
Point cloud is a basic description of discrete shape information. Parameterization of unorganized points is important for shape analysis and shape reconstruction of natural objects. In this paper we present a new algorithm for global parameterization of an unorganized point cloud and its application to the meshing of the cloud. Our method is guided by(More)
Point data are basic media for shape information acquisition and representation. A new approach is presented for global parameterization of unorganized point data and application to the meshing of point models with noises. While most of recent researches focus on quadrangulation of mesh models, it is extended to point models in this work, so as to loosely(More)
In this paper, we propose a novel method to reconstruct Chinese ancient architecture from incomplete point cloud obtained from multi-view reconstruction approach. The proposed method utilizes both global symmetry and partial symmetry to complete the missing part in the original point cloud. First global symmetry is extracted automatically and a matching(More)
In this paper, we create a virtual character that interacts with human player in a sword-fighting task. The data taken from a human player waving a stick as the 'sword' is mapped into the virtual environment, and the result of the collision detection during the virtual interaction is used as a reward for the reinforcement learning. We train a Q-network that(More)
In this paper, we propose a new approach on sampling and surface reconstruction of large-scale point cloud data. The sampling method is for huge point cloud data using spatial curve order and the surface reconstruction approach being based on witness complex theory. The approach first reorders the point cloud according to the spatial curve order and then(More)
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