14532857
Projecting registration error for accurate registration of overlapping range images
Abstract In this paper, we propose a novel algorithm for the automatic registration of two overlapping range images. Since it is relatively difficult to compare the registration errors of different point matches, we project them onto a virtual image plane for more accurate comparison using the classical pin-hole perspective projection camera model. While the traditional ICP algorithm is more interested in the points in the second image close to the sphere centred at the transformed point, the novel algorithm is more interested in the points in the second image as collinear as possible to the transformed point. The novel algorithm then extracts useful information from both the registration error and projected error histograms for the elimination of false matches without any feature extraction, image segmentation or the requirement of motion estimation from outliers corrupted data and, thus, has an advantage of easy implementation. A comparative study based on real images captured under typical imaging conditions has shown that the novel algorithm produces good registration results.
15266073
Improving ICP with easy implementation for free-form surface matching
Automatic range image registration and matching is an attractive but unresolved problem in both the machine vision and pattern recognition literature. Since automatic range image registration and matching is inherently a very difficult problem, the algorithms developed are becoming more and more complicated. In this paper, we propose a novel practical algorithm for automatic free-form surface matching. This method directly manipulates the possible point matches established by the traditional ICP criterion based on both the collinearity and closeness constraints without any feature extraction, image pre-processing, or motion estimation from outliers corrupted data. A comparative study based on a large number of real range images has shown the accuracy and robustness of the novel algorithm.
18353926
Inverse validation for accurate range image registration with structured data
Automatic range image registration is a fundamental yet extremely difficult problem in machine vision. In this paper, we extend a promising registration algorithm, the geometric iterative closest point (GICP), for structured image data. The extended algorithm is based on a relaxation method combining the motion estimation results from the possible correspondences established by the GICP algorithm and those that are further evaluated by an inverse validation procedure. A comparative study based on real images has shown that the extended algorithm is more accurate and robust than the original algorithm.
36759557
Geometrical analysis of two sets of 3D correspondence data patterns
Given two sets of image correspondence data, the analysis of the corresponding rigid body transformation that accurately describes the object's motion in 3D space is a fundamental problem in image understanding. While many methods have been put forward to analyse 3D transformations, such methods do not make use of the vector distance between feature points and angular information as constraints to analyse transformation parameters. Current methods and algorithms have also suffered from the problems of lack of efficiency, sensitivity to noise, and multiplicity of solutions. In this paper we present a novel geometrical analysis of rigid body transformations and a novel algorithm to calibrate transformation parameters based on image correspondence. The algorithm is validated through experimental calibration and a comparison is made with calibration implemented by the least squares method. We demonstrate that the proposed algorithm works well in the presence of noise and that its performance is in general superior to algorithms based on the least squares method.
18654744
Evaluating collinearity constraint for automatic range image registration
While most of the existing range image registration algorithms either have to extract and match structural (geometric or optical) features or have to estimate the motion parameters of interest from outliers corrupted point correspondence data for the elimination of false matches in the process of image registration, the registration error and the collinearity error derived directly from the traditional closest point criterion are also capable of doing the same job. However, the latter has an advantage of easy implementation. The purpose of this paper is to investigate which definition of collinearity is more accurate and stable in eliminating false matches inevitably introduced by the closest point criterion. The experiments based on real images show the advantages and disadvantages of different definitions of collinearity.
26921590
Evaluating structural constraints for accurate range image registration
New technological developments in optics and electronics are rendering laser scanning systems cheaper and more accurate. Such systems can directly capture depth information from objects simplifying range image analysis and enlarging their applications scope. Accurate image registration algorithms represent a pivotal aspect of range image analysis which still require substantial improvements. While a large number of algorithms have been proposed, it is very important to compare the performance of different registration algorithms so that good algorithms can be selected for real applications. Unfortunately, most of these algorithms are iterative with a number of parameters initialised by users. The main disadvantages of these methods are that these parameters are often context dependent. Thus, while aiming to develop automatic registration algorithms instead of comparing the registration algorithms themselves, we compare the structural constraints based on a single registration algorithm(GICP). A large number of experiments using real range images demonstrate their effectiveness on improving the GICP algorithm.
27650319
Generalized Bicycles
Let G = (V,E) be a graph with IZ vertices, and let A4 be a (left) module over a principal ideal domain D. Let Wo(A4) and WI(M) denote the modules of all vertex and edge weightings over M, respectively. An incidence weighting q of G is a weighting of each incident vertex-edge pair (u,e) with an element of D. Now consider an orientation of the edges of G. Let 6, denote the linear operator from We(M) to WI(M) given by 6,(w)(e) = q(u,e)w(u) yl(a,e)w(a), where e E E and u and 1: denote the tail and head of e, respectively. An v-cocycle is a weighting c E WI(M), such that c = 6(w) for some w c We(M). An q-bicycle is an q-cocycle that is also a cycle (ordinary bicycles are obtained when q E 1). Let B,(M) denote the module of all vertex weightings b E We(M), such that 6,(b) is an q-bicycle. For T a spanning tree rooted at vertex c, let q(T) denote the product of q(u,e) over all the edges e of T, where u denotes the end vertex of e that is further from u in T. The q-complexity Z~ of G is the vertex weighting over D, such that 74(c’) is the sum of q(T) over all spanning trees T rooted at t’. In this paper, we show that B,(M) ” M if, and only if 7,,m is nonzero for every nonzero m t M. Further if B,(M) 2 M then B,(M) = { z,,m : m E M}. As special cases of this formula, we obtain results about bicycles, balanced vertex weightings, resistive and leaky electrical networks, handicap ranking of tournaments, and Markov chains. The gcd q-complexity t,, is the greatest common divisor of (7411) : u E V}. We show that t, has a factorization t, = tl t2 t+l, unique up to multiplication by units of D, such that t,+l divides t, and such that for every module M over D, B,(M) is isomorphic to the direct sum of M and the submodules M(t,) = {m E A4 : t,m = 0}, i = 1,. , n 1. The latter formula generalizes the bicycle isomorphism formula given in Berman (1986).
2900427
Reconstructing B-spline Curves from Point Clouds--A Tangential Flow Approach Using Least Squares Minimization
We present a novel algorithm based on least-squares minimization to approximate point cloud data in 2D plane with a smooth B-spline curve. The point cloud data may represent an open curve with self intersection and sharp corner. Unlike other existing methods, such as the moving least-squares method and the principle curve method, our algorithm does not need a thinning process. The idea of our algorithm is intuitive and simple - we make a B-spline curve grow along the tangential directions at its two end-points following local geometry of point clouds. Our algorithm generates appropriate control points of the fitting B-spline curve in the least squares sense. Although presented for the 2D case, our method can be extended in a straightforward manner to fitting data points by a B-spline curve in higher dimensions
163835
Popularity Adaptive Search in Hybrid P2P Systems
In a hybrid peer-to-peer (P2P) system, flooding and DHT are both employed for content locating. The decision to use flooding or DHT largely depends on the population of desired data. Previous works either use local information only, or do not consider dynamic factors of P2P systems. In this paper, we propose a popularity adaptive search method for hybrid (PASH) P2P systems. By dynamically detecting the content popularity, PASH properly selects search methods and efficiently saves query traffic cost and response time. We comprehensively evaluate PASH through synthetic and trace-driven simulations. The results show that PASH outperforms existing approaches and it also scales well.
1966938
Robust midsagittal plane extraction from normal and pathological 3-D neuroradiology images
This paper focuses on extracting the ideal midsagittal plane (iMSP) from three-dimensional (3-D) normal and pathological neuroimages. The main challenges in this work are the structural asymmetry that may exist in pathological brains, and the anisotropic, unevenly sampled image data that is common in clinical practice. We present an edge-based, cross-correlation approach that decomposes the plane fitting problem into discovery of two-dimensional symmetry axes on each slice, followed by a robust estimation of plane parameters. The algorithm's tolerance to brain asymmetries, input image offsets and image noise is quantitatively evaluated. We find that the algorithm can extract the iMSP from input 3-D images with 1) large asymmetrical lesions; 2) arbitrary initial rotation offsets; 3) low signal-to-noise ratio or high bias field. The iMSP algorithm is compared with an approach based on maximization of mutual information registration, and is found to exhibit superior performance under adverse conditions. Finally, no statistically significant difference is found between the midsagittal plane computed by the iMSP algorithm and that estimated by two trained neuroradiologists.
15500512
Real-time simulation of physically based on-surface flow
Although many papers have been published in the field of fluid simulation, little attention has been paid to on-surface flow involving wetting and stain transportation as well as erosion and deposition phenomena. In this paper, we introduce nonzero divergence in the mass equation of Navier–Stokes equations to simulate water penetration from on-surface flow into substrate material. Also, the volume of fluid method is adopted to track the free surface. With a computation of the actual amount of absorbed water we render the wetting effects with fully dry and fully wet texture images simultaneously. Using our model, the on-surface flow that accompanies water absorption can be simulated realistically in real time with OpenGL preview rendering. Experimental results illustrate that our model can be widely applied to solve various problems related to on-surface flow.