5320148
Synthesizing bidirectional texture functions for real-world surfaces
In this paper, we present a novel approach to synthetically generating bidirectional texture functions (BTFs) of real-world surfaces. Unlike a conventional two-dimensional texture, a BTF is a six-dimensional function that describes the appearance of texture as a function of illumination and viewing directions. The BTF captures the appearance change caused by visible small-scale geometric details on surfaces. From a sparse set of images under different viewing/lighting settings, our approach generates BTFs in three steps. First, it recovers approximate 3D geometry of surface details using a shape-from-shading method. Then, it generates a novel version of the geometric details that has the same statistical properties as the sample surface with a non-parametric sampling method. Finally, it employs an appearance preserving procedure to synthesize novel images for the recovered or generated geometric details under various viewing/lighting settings, which then define a BTF. Our experimental results demonstrate the effectiveness of our approach.
10850316
Modeling realistic virtual hairstyles
The author presents an effective method for modeling realistic curly hairstyles, taking into account both artificial hairstyling processes and natural curliness. The result is a detailed geometric model of hairs that can be rendered and animated via existing methods. Our technique exploits the analogy between hairs and a vector field; it interactively and efficiently models global and local hair flows by superimposing procedurally defined vector field primitives that have local influence. Usually only a very small number of vector field primitives are needed to model a complicated hairstyle. An initial model of hair strands is extracted from the superimposed vector fields by tracing their field lines. Random natural or artificial curliness can be added to the initial model through a parametric hair offset function with a randomized distribution of parameters over the scalp. Techniques for shearing and clustering are also designed to improve the overall appearance of the hair model. Our technique has been successfully applied to generate a variety of realistic hairstyles with different curliness and length distributions.
1542177
Out-of-core tensor approximation of multi-dimensional matrices of visual data
Tensor approximation is necessary to obtain compact multilinear models for multi-dimensional visual datasets. Traditionally, each multi-dimensional data item is represented as a vector. Such a scheme flattens the data and partially destroys the internal structures established throughout the multiple dimensions. In this paper, we retain the original dimensionality of the data items to more effectively exploit existing spatial redundancy and allow more efficient computation. Since the size of visual datasets can easily exceed the memory capacity of a single machine, we also present an out-of-core algorithm for higher-order tensor approximation. The basic idea is to partition a tensor into smaller blocks and perform tensor-related operations blockwise. We have successfully applied our techniques to three graphics-related data-driven models, including 6D bidirectional texture functions, 7D dynamic BTFs and 4D volume simulation sequences. Experimental results indicate that our techniques can not only process out-of-core data, but also achieve higher compression ratios and quality than previous methods.
46180
Efficient visibility processing for projective texture mapping
Abstract Projective texture mapping is a powerful tool for image-based rendering. However, visibility information must be obtained in order to project correct textures onto the geometric sturcture. This paper presents a novel visibility algorithm for determining which polygons are visible from each camera position. It has object-space precision, but operates in both image-space and object-space to get better performance. It generates much less polygons than traditional object-space algorithms to help accelerate the speed of texture mapping. The techniques used to achieve these are conservative image-space occlusion testing and object-space shallow clipping . This algorithm has been successfully used to generate large-scale image-based rendering of a whole university campus, and image-based rendering of architectures under dynamic lighting.
13948350
Feature matching and deformation for texture synthesis
One significant problem in patch-based texture synthesis is the presence of broken features at the boundary of adjacent patches. The reason is that optimization schemes for patch merging may fail when neighborhood search cannot find satisfactory candidates in the sample texture because of an inaccurate similarity measure. In this paper, we consider both curvilinear features and their deformation. We develop a novel algorithm to perform feature matching and alignment by measuring structural similarity. Our technique extracts a feature map from the sample texture, and produces both a new feature map and texture map. Texture synthesis guided by feature maps can significantly reduce the number of feature discontinuities and related artifacts, and gives rise to satisfactory results.
13369249
Reconstruction of 3-D Symmetric Curves from Perspective Images without Discrete Features
The shapes of many natural and man-made objects have curved contours. The images of such contours usually do not have sufficient distinctive features to apply conventional feature-based reconstruction algorithms. This paper shows that both the shape of curves in 3-D space and the camera poses can be accurately reconstructed from their perspective images with unknown point correspondences given that the curves have certain invariant properties such as symmetry. We show that in such cases the minimum number of views needed for a solution is remarkably small: one for planar curves and two for nonplanar curves (of arbitrary shapes), which is significantly less than what is required by most existing algorithms for general curves. Our solutions rely on minimizing the L 2-distance between the shapes of the curves reconstructed via the “epipolar geometry” of symmetric curves. Both simulations and experiments on real images are presented to demonstrate the effectiveness of our approach.
1353091
A Lightweight Approach to Semantic Web Service Synthesis
Web service technologies are becoming a new paradigm for distributed computing. With increasing number of web services available on the internet, there is an urgent need for information brokers that can autonomously integrate web services on behalf of a user. To this end, we propose web service specification, which defines what the service is but not how the service is implemented, and service synthesizer, which can dynamically synthesize the implementation of the specification from existing web services over the web.
36949782
Adaptation of the transfer function of the Hodgkin-Huxley (HH) neuronal model
Abstract The transfer functions of sensory neurons are known to adapt to the statistics of the input signals. It is however unclear whether such adaptation arises from the nonlinear dynamics of the neuron or emerges from the collective interaction among neurons embedded in a network. We investigated the Hodgkin–Huxley (HH) neuronal model's response to Gaussian white noise signals of different variances and found that the recovered kernel adapt its preferred temporal frequency and its energy gains according to noise variance. This adaptation is likely a consequence of the cooperative interaction between the noises and the bifurcation dynamics of the neurons.
723568
A Bayesian Network Approach to Ontology Mapping
This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling uncertainty in semantic web. In this approach, the source and target ontologies are first translated into Bayesian networks (BN); the concept mapping between the two ontologies are treated as evidential reasoning between the two translated BNs. Probabilities needed for constructing conditional probability tables (CPT) during translation and for measuring semantic similarity during mapping are learned using text classification techniques where each concept in an ontology is associated with a set of semantically relevant text documents, which are obtained by ontology guided web mining. The basic ideas of this approach are validated by positive results from computer experiments on two small real-world ontologies.
44493552
Adaptation of the temporal receptive fields of macaque V1 neurons
Abstract Traditional view of macaque V1 neurons is that they are static spatiotemporal filters. This study shows that V1 neurons’ temporal receptive fields (kernels) are dynamic and adaptive. In order to study the adaptation of the kernels to a variety of stimuli, we developed a regression approach to recover kernels using naturalistic stimuli. Using this technique, we studied how the kernels of the V1 neurons in macaque monkeys adapt to the frequency bandwidth of naturalistic signals. We found that the temporal frequency tunings and the gains of the receptive fields of the neurons change according to the statistical context of the stimulus environment.
40955801
Polarimetric SAR image segmentation using texture partitioning and statistical analysis
This paper presents a new technique for partitioning polarimetric synthetic aperture radar (POL-SAR) imagery into regions of homogeneous polarimetric backscattering properties. The method consists of two cascaded steps: an initial texture segmentation of one image derived from the POL-SAR data, and a polarimetric statistical region merging process that refines and modifies the initial segmentation. In the first stage, a morphological region-based image partitioning technique, the watershed algorithm, plays the key role. While in the second stage, the region adjacency graph and the segment dissimilarity measures derived from the Wishart model and the K distribution are applied. The overall segmentation algorithm has been tested using real 4-look POL-SAR imagery and sample results are provided in the paper. The main innovation of this work is the utilization of the K distribution in the segmentation process.