A survey of visual preprocessing and shape representation techniques

Many recent theories and methods proposed for visual preprocessing and shape representation are summarized. The survey brings together research from the fields of biology, psychology, computer science, electrical engineering, and most recently, neural networks. It was motivated by the need to preprocess images for a sparse distributed memory (SDM), but the techniques presented may also prove useful for applying other associative memories to visual pattern recognition. The material of this survey is divided into three sections: an overview of biological visual processing; methods of preprocessing (extracting parts of shape, texture, motion, and depth); and shape representation and recognition (form invariance, primitives and structural descriptions, and theories of attention)

Lipid and Protein Organizations in Model Membrane Systems- Membrane Curvature, Lipid Structure, Domain Formation, and Membrane Binding Kinetics

The composition and morphology of cellular membranes are highly dynamic. Potential parameters modulating protein and lipid distributions in different organelles include membrane shapes and the structures of lipids and proteins. Moreover, the concept of lipid rafts provides a prevailing view where nanodomains serve as centers for signal transduction, membrane trafficking, and cytoskeletal organization. In this contribution, we first investigated the lipid and protein organizations as a function of membrane curvature. To this end, a system consisting of solid-supported wavy membranes that exhibits a continuous curvature distribution with positive and negative curvature ranges was fabricated. Spatial distributions of ENTH (epsin N-terminal homology) domain and N-BAR (Bin-Amphiphysin-Rvs) domains derived from the proteins Endophilin and BIN-1 were found to vary approximately linearly with membrane curvature. In contrast, streptavidin and fluorescent lipid analogues exhibited homogenous distributions on wavy membranes. Fluorescence recovery after photobleaching and single-molecule tracking experiments revealed that protein domains remain laterally fluid in the curved regions. We next studied the membrane organization with respect to lipid structures, more specifically, the length and degree of saturation of acyl chains of lipids. The ganglioside GM1 binds cholera toxin (CT) on host cells and carries it retrograde from the plasma membrane (PM) through endosomes, the trans-Golgi network (TGN), and the endoplasmic reticulum (ER) to induce toxicity. To elucidate how a membrane lipid can specify trafficking in these pathways, GM1 isoforms with alternate ceramide domains were synthesized and their partitioning between liquid-ordered (Lo) and liquid-disordered (Ld) phases in GUVs was imaged. GM1 with differing ceramides showed distinct phase-partitioning behaviors. Furthermore, crosslinking of GM1 by cholera toxin subunit B (CTB) was found to drive phase partitioning shift from less preferential phase preference to exclusively Ld or Lo phases. To shed light on the stability of lipid domains, factors qwhich affect line tension were discussed and potential line-active molecules were examined. We found that the presence of cone-shaped diacylglycerol decreases line tension, while the commonly used fluorescent lipid, Texas-Red DHPE tends to increase line tension. Additionally, to bridge the connection between thermodynamics to highly dynamic cellular environments, we developed a single liposome-based kinetics system which allowed us to examine membrane binding kinetics of proteins as a function of membrane curvature. Overall, these measurements help provide an integrated view of biophysical and structural parameters underlying organizations of lipids and proteins

Automatic Landmarking for Non-cooperative 3D Face Recognition

This thesis describes a new framework for 3D surface landmarking and evaluates its performance for feature localisation on human faces. This framework has two main parts that can be designed and optimised independently. The first one is a keypoint detection system that returns positions of interest for a given mesh surface by using a learnt dictionary of local shapes. The second one is a labelling system, using model fitting approaches that establish a one-to-one correspondence between the set of unlabelled input points and a learnt representation of the class of object to detect. Our keypoint detection system returns local maxima over score maps that are generated from an arbitrarily large set of local shape descriptors. The distributions of these descriptors (scalars or histograms) are learnt for known landmark positions on a training dataset in order to generate a model. The similarity between the input descriptor value for a given vertex and a model shape is used as a descriptor-related score. Our labelling system can make use of both hypergraph matching techniques and rigid registration techniques to reduce the ambiguity attached to unlabelled input keypoints for which a list of model landmark candidates have been seeded. The soft matching techniques use multi-attributed hyperedges to reduce ambiguity, while the registration techniques use scale-adapted rigid transformation computed from 3 or more points in order to obtain one-to-one correspondences. Our final system achieves better or comparable (depending on the metric) results than the state-of-the-art while being more generic. It does not require pre-processing such as cropping, spike removal and hole filling and is more robust to occlusion of salient local regions, such as those near the nose tip and inner eye corners. It is also fully pose invariant and can be used with kinds of objects other than faces, provided that labelled training data is available

3D shape matching and registration : a probabilistic perspective

Dense correspondence is a key area in computer vision and medical image analysis. It has applications in registration and shape analysis. In this thesis, we develop a technique to recover dense correspondences between the surfaces of neuroanatomical objects over heterogeneous populations of individuals. We recover dense correspondences based on 3D shape matching. In this thesis, the 3D shape matching problem is formulated under the framework of Markov Random Fields (MRFs). We represent the surfaces of neuroanatomical objects as genus zero voxel-based meshes. The surface meshes are projected into a Markov random field space. The projection carries both geometric and topological information in terms of Gaussian curvature and mesh neighbourhood from the original space to the random field space. Gaussian curvature is projected to the nodes of the MRF, and the mesh neighbourhood structure is projected to the edges. 3D shape matching between two surface meshes is then performed by solving an energy function minimisation problem formulated with MRFs. The outcome of the 3D shape matching is dense point-to-point correspondences. However, the minimisation of the energy function is NP hard. In this thesis, we use belief propagation to perform the probabilistic inference for 3D shape matching. A sparse update loopy belief propagation algorithm adapted to the 3D shape matching is proposed to obtain an approximate global solution for the 3D shape matching problem. The sparse update loopy belief propagation algorithm demonstrates significant efficiency gain compared to standard belief propagation. The computational complexity and convergence property analysis for the sparse update loopy belief propagation algorithm are also conducted in the thesis. We also investigate randomised algorithms to minimise the energy function. In order to enhance the shape matching rate and increase the inlier support set, we propose a novel clamping technique. The clamping technique is realized by combining the loopy belief propagation message updating rule with the feedback from 3D rigid body registration. By using this clamping technique, the correct shape matching rate is increased significantly. Finally, we investigate 3D shape registration techniques based on the 3D shape matching result. Based on the point-to-point dense correspondences obtained from the 3D shape matching, a three-point based transformation estimation technique is combined with the RANdom SAmple Consensus (RANSAC) algorithm to obtain the inlier support set. The global registration approach is purely dependent on point-wise correspondences between two meshed surfaces. It has the advantage that the need for orientation initialisation is eliminated and that all shapes of spherical topology. The comparison of our MRF based 3D registration approach with a state-of-the-art registration algorithm, the first order ellipsoid template, is conducted in the experiments. These show dense correspondence for pairs of hippocampi from two different data sets, each of around 20 60+ year old healthy individuals

Characterization of wettability in porous media using the lattice boltzmann method

This thesis is concerned with multiphase flow in porous media, focusing primarily on applications to oil recovery from subsurface rocks. The wettability of crude oil-brine-rock systems in petroleum reservoirs often exhibits mixed-wet states where effective contact angle varies locally, because surface active components such as asphaltenes in the crude oil can alter the wettability from its original water-wet to more oil-wet states. Furthermore, when a lower salinity brine than that of formation brine is injected to displace oil, which is known as low salinity water flooding, wettability alteration from a mixed-wet state to more water-wet condition can occur, resulting in an improvement of oil recovery. We use direct numerical simulation to study the impact of wettability and its alteration on multiphase flow in porous media at the pore-scale. A numerical model is constructed based on the lattice Boltzmann method with two newly developed numerical methods: a wetting boundary condition which precisely models contact angle, and a model to capture wettability alteration which changes contact angle depending on the computed local salinity. The numerical model is validated using several test cases where analytical solutions are available. In particular, the new wetting boundary condition is extensively validated using the static test cases of a flat, curved and staircase solid surfaces, and a dynamic test case of capillary rise. Water flooding in mixed-wet media is studied using the numerical model. Water flooding experiments imaged with a micro-CT by Alhammadi et al. are used in which hundreds of thousands of geometrically measured in situ contact angles are available using the method of AlRatrout et al. We show that a good agreement in both the fluid configurations and effective water permeability is obtained when we model the spatial distribution of contact angle on a pore-by-pore basis, but using higher contact angles than those measured in oil-wet regions of the pore space. This physically makes sense because the contact angle to use in simulations is the locally largest value that determines the threshold capillary pressure, whereas the geometrically measured angle may represent a hinging value on pores where displacement has not occurred. Using the matched simulation model to the water flooding experiments of Alhammadi et al., we study three enhanced oil recovery (EOR) methods -- low salinity water flooding, surfactant flooding, and polymer flooding -- through a parametric study changing fluid and/or rock properties of the simulation. This illustrates the use of a simulation model, namely to predict the behavior outside the range studied experimentally. We show the impact of these enhanced oil recovery methods on the microscopic displacement efficiency of the rock. Although this study does not consider the mixing between brine originally in the pore space and injected EOR fluids, this mixing is modeled for low salinity water flooding in the next study, using the two-phase lattice Boltzmann model coupled with mass transport of ions in water. We study wettability alteration caused by exposure to low salinity water using the new wettability alteration model. The numerical model is validated using two experiments performed at the pore-scale: detachment of oil droplets exposed to low salinity water by Mahani et al., and low salinity water flooding on a sinusoidal micro-model by Bartels et al. The phenomena observed in the experiments, including wettability alteration, detachment of oil droplets and recovery of trapped oil, are successfully simulated using a progressive wettability alteration driven by the slow development of thin water films implemented in the numerical model. The numerical model is, then, applied to micro-CT images of a Bentheimer sandstone. Higher oil recovery is observed in secondary mode injection compared to that of tertiary mode, whose mechanism is explained based on the simulation results, where a more stable displacement front is seen for secondary flooding. Lastly, we use the numerical model to validate recently developed pore-scale image analysis methods. A method to measure the interfacial curvature to obtain capillary pressure is studied. Through a comparison between measured curvature and curvature obtained from the simulated capillary pressure, the validation of the method and the assessment of its uncertainty is presented. We, then, validate a method to measure a thermodynamic contact angle by Blunt et al., through a comparison between the input contact angle of the simulations and the thermodynamic contact angle found from the simulated fluid configurations. Furthermore, we demonstrate how to use this method on a pore-by-pore basis to obtain the spatial distribution of wettability. We show that in mixed-wet media we can accurately capture the variation in local contact angle. Significant discrepancies are only seen in less consolidated media where the invading meniscus straddles several pores. Overall the thesis provides an improved method for direct simulation of flow in porous media which have undergone a wettability alteration. The work has been used to interpret experimental work and make predictions for local displacement efficiency for enhanced oil recovery processes. It has also been used to suggest methodologies to measure curvature and wettability from pore-scale imaging experiments.Open Acces

Numerical Ricci-flat metrics on K3

We develop numerical algorithms for solving the Einstein equation on Calabi-Yau manifolds at arbitrary values of their complex structure and Kahler parameters. We show that Kahler geometry can be exploited for significant gains in computational efficiency. As a proof of principle, we apply our methods to a one-parameter family of K3 surfaces constructed as blow-ups of the T^4/Z_2 orbifold with many discrete symmetries. High-resolution metrics may be obtained on a time scale of days using a desktop computer. We compute various geometric and spectral quantities from our numerical metrics. Using similar resources we expect our methods to practically extend to Calabi-Yau three-folds with a high degree of discrete symmetry, although we expect the general three-fold to remain a challenge due to memory requirements.Comment: 38 pages, 10 figures; program code and animations of figures downloadable from http://schwinger.harvard.edu/~wiseman/K3/ ; v2 minor corrections, references adde

Acquisition and modeling of 3D irregular objects.

by Sai-bun Wong.Thesis (M.Phil.)--Chinese University of Hong Kong, 1994.Includes bibliographical references (leaves 127-131).Abstract --- p.vAcknowledgment --- p.viiChapter 1 --- Introduction --- p.1-8Chapter 1.1 --- Overview --- p.2Chapter 1.2 --- Survey --- p.4Chapter 1.3 --- Objectives --- p.6Chapter 1.4 --- Thesis Organization --- p.7Chapter 2 --- Range Sensing --- p.9-30Chapter 2.1 --- Alternative Approaches to Range Sensing --- p.9Chapter 2.1.1 --- Size Constancy --- p.9Chapter 2.1.2 --- Defocusing --- p.11Chapter 2.1.3 --- Deconvolution --- p.14Chapter 2.1.4 --- Binolcular Vision --- p.18Chapter 2.1.5 --- Active Triangulation --- p.20Chapter 2.1.6 --- Time-of-Flight --- p.22Chapter 2.2 --- Transmitter and Detector in Active Sensing --- p.26Chapter 2.2.1 --- Acoustics --- p.26Chapter 2.2.2 --- Optics --- p.28Chapter 2.2.3 --- Microwave --- p.29Chapter 2.3 --- Conclusion --- p.29Chapter 3 --- Scanning Mirror --- p.31-47Chapter 3.1 --- Scanning Mechanisms --- p.31Chapter 3.2 --- Advantages of Scanning Mirror --- p.32Chapter 3.3 --- Feedback of Scanning Mirror --- p.33Chapter 3.4 --- Scanning Mirror Controller --- p.35Chapter 3.5 --- Point-to-Point Scanning --- p.39Chapter 3.6 --- Line Scanning --- p.39Chapter 3.7 --- Specifications and Measurements --- p.41Chapter 4 --- The Rangefinder with Reflectance Sensing --- p.48-58Chapter 4.1 --- Ambient Noises --- p.49Chapter 4.2 --- Occlusion/Shadow --- p.49Chapter 4.3 --- Accuracy and Precision --- p.50Chapter 4.4 --- Optics --- p.53Chapter 4.5 --- Range/Reflectance Crosstalk --- p.56Chapter 4.6 --- Summary --- p.58Chapter 5 --- Computer Generation of Range Map --- p.59-75Chapter 5.1 --- Homogenous Transformation --- p.61Chapter 5.2 --- From Global to Viewer Coordinate --- p.63Chapter 5.3 --- Z-buffering --- p.55Chapter 5.4 --- Generation of Range Map --- p.66Chapter 5.5 --- Experimental Results --- p.68Chapter 6 --- Characterization of Range Map --- p.76-90Chapter 6.1 --- Mean and Gaussian Curvature --- p.76Chapter 6.2 --- Methods of Curvature Generation --- p.78Chapter 6.2.1 --- Convolution --- p.78Chapter 6.2.2 --- Local Surface Patching --- p.81Chapter 6.3 --- Feature Extraction --- p.84Chapter 6.4 --- Conclusion --- p.85Chapter 7 --- Merging Multiple Characteristic Views --- p.91-119Chapter 7.1 --- Rigid Body Model --- p.91Chapter 7.2 --- Sub-rigid Body Model --- p.94Chapter 7.3 --- Probabilistic Relaxation Matching --- p.95Chapter 7.4 --- Merging the Sub-rigid Body Model --- p.99Chapter 7.5 --- Illustration --- p.101Chapter 7.6 --- Merging Multiple Characteristic Views --- p.104Chapter 7.7 --- Mislocation of Feature Extraction --- p.105Chapter 7.7.1 --- The Transform Matrix for Perfect Matching --- p.106Chapter 7.7.2 --- Introducing The Errors in Feature Set --- p.108Chapter 7.8 --- Summary --- p.113Chapter 8 --- Conclusion --- p.120-126References --- p.127-131Appendix A - Projection of Object --- p.A1-A2Appendix B - Performance Analysis on Rangefinder System --- p.B1-B16Appendix C - Matching of Two Characteristic views --- p.C1-C