We introduce a stochastic algorithm for pairwise affine registration of partially overlapping 3D point clouds with unknown point correspondences. The algorithm recovers the globally optimal scale, rotation, and transl...
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In today’s world of rapid technological advancement, we find an increasing demand for low-cost systems that are capable of fast and easy generation of realistic avatars for use in Virtual Reality (VR) applications. F...
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We present a robust approach for reconstructing the architectural structure of complex indoor environments given a set of cluttered input scans. Our method first uses an efficient occlusion-aware process to extract pl...
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We present a robust approach for reconstructing the architectural structure of complex indoor environments given a set of cluttered input scans. Our method first uses an efficient occlusion-aware process to extract planar patches as candidate walls, separating them from clutter and coping with missing data. Using a diffusion process to further increase its robustness, our algorithm is able to reconstruct a clean architectural model from the candidate walls. To our knowledge, this is the first indoor reconstruction method which goes beyond a binary classification and automatically recognizes different rooms as separate components. We demonstrate the validity of our approach by testing it on both synthetic models and real-world 3D scans of indoor environments.
In this demo, a performance driven 3D face animation system is proposed. The proposed system consists of two key components: a robust non-rigid 3D tracking module and a MPEG4 compliant facial animation module. Firstly...
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ISBN:
(纸本)9781605586083
In this demo, a performance driven 3D face animation system is proposed. The proposed system consists of two key components: a robust non-rigid 3D tracking module and a MPEG4 compliant facial animation module. Firstly, the facial motion is tracked from source videos which contain both the rigid 3D head motion (6 DOF) and the non-rigid expression variations. Afterward, the tracked facial motion is parameterized via estimating a set of MPEG4 facial animation parameters(FAP). As the final step, these FAP values are transferred to the MPEG4-compliant face model for the animation purpose. The proposed tracking and animation system has a strong generalization ability and can be used in the indoor environment with no additional assumptions.
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