10333672
Facets: a new algorithm for extracting 3-D surface from volume data
Three dimensional surface reconstruction from volume data is very useful in medical imaging, scientific visualization and geometric modeling. Given a set of uniform sampled 3-D volume data, the problem of surface construction is to interpolate or approximate the three dimensional surface from it. A simple and efficient method, Facets, is proposed to extract the accurate and continuous surface with consistent topology.
117805231
Hierarchical methods for three-dimensional surface reconstruction
Surface reconstruction from raw data such as volume data, implicit functions, and scattered data in three-dimensional space is very useful in medical imaging, scientific visualization, and geometric modeling. In this study, several surface reconstruction techniques are investigated. A new surface reconstruction technique and several interpolation schemes are introduced for processing the volume data. A new hierarchical scheme for extracting three-dimensional surfaces from volume data is presented. The hierarchical scheme is used to visualize different levels of surface detail allowing a user to explore different features of the surface at different scales. Estimated surface curvature is used as a smoothness condition, and the distance measurement between different levels of surfaces constructed is used as a stopping criterion. The volume pyramid used by the hierarchical scheme was built and tested by two different data structures: an octree and wavelet transforms. The hierarchical method using three-dimensional wavelet transforms is also useful in multiresolution surface analysis. An adaptive hierarchical method using an octree is implemented to increase the accuracy of the surface by adaptively subdividing regions of high curvature using an appropriate interpolation scheme without substantially increasing the number of polygons.
27987792
The Study and Analysis of Joint Adaptive Clock Recovery Mechanism for TDMoIP
TDM over IP (TDMoIP) is an effective method for transparently transporting time division multiplexed (TDM) signals over IP-based networks. Clock recovery mechanism is essential for it. This paper briefly introduces the Timing requirement and principle of clock recovery, describes an improved adaptive clock recovery mechanism combined with timestamps and buffer data offset, presents the derivational process and analyzes how to deal with IP-based networks characteristics. Finally, the simulation results showed that the performance of this improved clock recovery mechanism can reach a high level and meet the requirement of the TDM service standard.
6932570
3D Surface Matching and Recognition Using Conformal Geometry
3D surface matching is a fundamental issue in computer vision with many applications such as shape registration, 3D object recognition and classification. However, surface matching with noise, occlusion and clutter is a challenging problem. In this paper, we analyze a family of conformal geometric maps including harmonic maps, conformal maps and least squares conformal maps with regards to 3D surface matching. As a result, we propose a novel and computationally efficient surface matching framework that uses least squares conformal maps. According to conformal geometry theory, each 3D surface with disk topology can be mapped to a 2D domain through a global optimization and the resulting map is a diffeomorphism, i.e., one-to-one and onto. This allows us to simplify the 3D surface-matching problem to a 2D image-matching problem, by comparing the resulting 2D conformal geometric maps, which are stable, insensitive to resolution changes and robust to occlusion and noise. Therefore, highly accurate and efficient 3D surface matching algorithms can be achieved by using conformal geometric maps. Finally, the performance of conformal geometric maps is evaluated and analyzed comprehensively in 3D surface matching with occlusion, noise and resolution variation. We also provide a series of experiments on real 3D face data that achieve high recognition rates.
8649500
3D Non-rigid Surface Matching and Registration Based on Holomorphic Differentials
3D surface matching is fundamental for shape registration, deformable 3D non-rigid tracking, recognition and classification. In this paper we describe a novel approach for generating an efficient and optimal combined matching from multiple boundary-constrained conformal parameterizations for multiply connected domains (i.e., genus zero open surface with multiple boundaries), which always come from imperfect 3D data acquisition (holes, partial occlusions, change of pose and non-rigid deformation between scans). This optimality criterion is also used to assess how consistent each boundary is, and thus decide to enforce or relax boundary constraints across the two surfaces to be matched. The linear boundary-constrained conformal parameterization is based on the holomorphic differential forms, which map a surface with n boundaries conformally to a planar rectangle with (n - 2) horizontal slits, other two boundaries as constraints. The mapping is a diffeomorphism and intrinsic to the geometry, handles an open surface with arbitrary number of boundaries, and can be implemented as a linear system. Experimental results are given for real facial surface matching, deformable cloth non-rigid tracking, which demonstrate the efficiency of our method, especially for 3D non-rigid surfaces with significantly inconsistent boundaries.
14397325
Constraint-Sensitive Privacy Management for Personalized Web-Based Systems
This research aims at reconciling web personalization with privacy constraints imposed by legal restrictions and by users' privacy preferences. We propose a software product line architecture approach, where our privacyenabling user modeling architecture can dynamically select personalization methods that satisfy current privacy constraints to provide personalization services. A feasibility study is being carried out with the support of an existing user modeling server and a software architecture based development environment.
18971548
Coverage-preserving Data Gathering in Wireless Sensor Networks
The power is the most significant resource in wireless sensor nodes, so energy conservation is the most important factor in designing the protocol for sensor networks. In this paper, we study the problem of energy-efficient collection of the physical information from the target area. The coverage-preserving data gathering (CPDG) problem is to build up a tree, which minimizes the total energy consumption, and preserves the original coverage to ensure the result correctness. This problem can be formalized as 0-1 integer linear programming, and solved by an efficient heuristic algorithm. Furthermore, an improved algorithm is also proposed to balance the energy consumption among all the sensor nodes. The experimental results show that CPDG algorithm can conserve the energy about 30% of PEDAP protocol, which is regarded as one of the most efficient data gathering protocols as we know.