Abstract How to establish the matching (or corresponding) between two different 3D shapes is a classical problem. This paper focused on the research on shape mapping of 3D mesh models, and proposed a shape mapping algorithm based on Hidden Markov Random Field and EM algorithm, as introducing a hidden state random variable associated with the adjacent blocks of shape matching when establishing H...

Using a probabilistic interpretation of an n dimensional extension of Papoulis's Generalized Sampling Theorem, an iterative algorithm has been devised for 3D reconstruction of a Lambertian surface at subpixel accuracy. The problem has been formulated as an optimization one in a Bayesian framework. The latter allows for introducing a priori information on the solution, using Markov Random Fields...

This paper proposes an efficient pairwise surface matching approach for the automatic assembly of 3d fragments or industrial components. The method rapidly scans through the space of all possible solutions by a special kind of random sample consensus (RANSAC) scheme. By using surface normals and optionally simple features like surface curvatures, we can highly constrain the initial 6 degrees of...

Enlarged perivascular spaces (EPVS) in the brain are an emerging imaging marker for cerebral small vessel disease, and have been shown to be related to increased risk of various neurological diseases, including stroke and dementia. Automatic quantification of EPVS would greatly help to advance research into its etiology and its potential as a risk indicator of disease. We propose a convolutiona...

The three-dimensional baroclinic quasigeostrophic ow model has been widely used to study basic mechanisms in oceanic ows and climate dynamics. In this paper, we consider this ow model under random wind forcing and time-periodic uctuations on uid boundary (the interface between the oceans and the atmosphere). The time-periodic uctuations are due to periodic rotation of the earth and thus periodi...

In this paper, a noble nonintrusive three-dimensional (3D) face modeling system for random-profile-based 3D face recognition is presented. Although recent two-dimensional (2D) face recognition systems can achieve a reliable recognition rate under certain conditions, their performance is limited by internal and external changes, such as illumination and pose variation. To address these issues, 3...

We study “tricolor percolation” on the regular tessellation of R by truncated octahedra, which is the three-dimensional analog of the hexagonal tiling of the plane. We independently assign one of three colors to each cell according to a probability vector p = (p1, p2, p3) and define a “tricolor edge” to be an edge incident to one cell of each color. The tricolor edges form disjoint loops and/or...

We propose a novel 3D neural network architecture for 3D hand pose estimation from a single depth image. Different from previous works that mostly run on 2D depth image domain and require intermediate or post process to bring in the supervision from 3D space, we convert the depth map to a 3D volumetric representation, and feed it into a 3D convolutional neural network(CNN) to directly produce t...

due to business and environmental issues, the efficient design of an integrated forward/reverse logistics network has recently attracted more attention from researchers. the significance of transportation cost and customer satisfaction spurs an interest in developing a flexible network design model with different delivery paths. this paper proposes a flexible mixed-integer programming model to ...