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We augment the tensor voting framework with a data-driven multiscale scheme for reconstructing a multiresolution mesh from a noisy 3D point set. The augmentations are effective, automatic but very simple, consisting of surface saliency inference, scale segmentation, and data normalization. These data analysis steps enable tensor voting to operate at a single scale in each normalized data segment,...
This paper proposes how the classic factorisation algorithm for affine reconstruction can be extended to be robust to outliers and proposes how the uncertainty analysis can be performed in this case. The robust estimation approach elaborated here is based on the iteratively re-weighted least-squares but the use of other robust methods is also discussed. Moreover, the uncertainty analysis presented...
We present an algorithm which can track the 3D pose of a hand held camera in real-time using predefined models of objects in the scene. The technique utilises and extends recently developed techniques for 3D tracking with a particle filter. The novelty is in the use of edge information for 3D tracking which has not been achieved before within a realtime Bayesian sampling framework. We develop a robust...
Statistical background modeling is a fundamental and important part of many visual tracking systems and of other computer vision applications. In this paper, we presents an effective and adaptive background modeling method for detecting foreground objects in both static and dynamic scenes. The proposed method computes SAmple CONsensus (SACON) of the background samples and estimates a statistical model...
A new method called two-dimensional Fisher discriminant analysis (2D-FDA) is proposed to deal with the small sample size (SSS) problem in LDA based face recognition. Then appearance and depth information are combined to improve face recognition rate. Different from the conventional 1D-FDA (PCA plus LDA) approaches, 2D-FDA is based on 2D image matrices rather than column vectors so the image matrix...
The modeling of human faces from single or multiple images can be solved by fitting an active appearance model (AAM). However, fitting such models with unknown prior estimation is a challenging task since shape and appearance are closely linked. In this paper, we address the efficiency of the sampling technique in regard to the shape alignment accuracy. The hybrid method we propose is based on a non-uniform...
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