10229132
Controllable motion synthesis in a gaseous medium
The generation of realistic motion satisfying user-defined requirements is one of the most important goals of computer animation. Our aim in this paper is the synthesis of realistic, controllable motion for lightweight natural objects in a gaseous medium. We formulate this problem as a large-scale spacetime optimization with user controls and fluid motion equations as constraints. We have devised novel and effective methods to make this large optimization tractable. Initial trajectories are generated with data-driven synthesis based on stylistic motion planning. Smoothed particle hydrodynamics (SPH) is used during optimization to produce fluid simulations at a reasonable computational cost, while interesting vortex-based fluid motion is generated by recording the presence of vortices in the initial trajectories and maintaining them through optimization. Object rotations are refined as a postprocess to enhance the visual quality of the results. We demonstrate our techniques on a number of animations involving single or multiple objects.
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.
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.
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.
11741866
An efficient implementation of linear-phase FIR filters for a rational sampling rate conversion
This paper considers how to efficiently implement linear-phase FIR filters for providing a sampling rate conversion by an arbitrary rational factor of M/L, where L(M) is the up-sampling (down-sampling) factor to be implemented before (after) the actual filter. In the proposed implementation, the coefficient symmetry of the linear-phase FIR filter is exploited as well as possible when taking into account the following facts. When increasing (decreasing) the sampling rate by the factor of L(M), only every Lth input sample has a nonzero value (only every Mth output sample has to be evaluated). The proposed implementation is, first, presented by two illustrative examples and, then, guidelines are given on how to efficiently implement a sampling rate converter having an arbitrary rational sampling rate factor M/L
53223698
Validating the result of a Quantified Boolean Formula (QBF) solver: theory and practice
2412157
Optimal adaptive bandwidth monitoring for QoS based retrieval
Network aware multimedia delivery applications are a class of applications that provide certain level of quality of service (QoS) guarantees to end users while not assuming underlying network resource reservations. These applications guarantee QoS parameters like media object transmission time limit by actively monitoring the available bandwidth of the network and adapting the object to a target size that can be transmitted within a given time limit. A critical problem is how to obtain an accurate enough estimation of available bandwidth while not wasting too much time in bandwidth testing. In this paper, we present an algorithm to determine optimal amount of bandwidth testing given a probabilistic confidence level for network-aware multimedia object retrieval applications. The model treats the bandwidth testing as sampling from an actual bandwidth population. It uses statistical estimation method to quantify the benefit of each new bandwidth-testing sample, which is used to determine the optimal amount of bandwidth testing by balancing the benefit with the cost of each sample. Our implementation and experiments shows the algorithm determines the optimal amount of bandwidth testing effectively with minimum computation overhead.
1624571
Non-uniform dependences partitioned by recurrence chains
Nonuniform distance loop dependences are a known obstacle to find parallel iterations. To find the outermost loop parallelism in these "irregular" loops, a novel method is presented based on recurrence chains. The scheme organizes nonuniformly dependent iterations into lexicographically ordered monotonic chains. While the initial and final iterations of monotonic chains form two parallel sets, the remaining iterations form an intermediate set that can be partitioned further. When there is only one pair of coupled array references, the nonuniform dependences are represented by a single recurrence equation. In that case, the chains in the intermediate set do not bifurcate and each can be executed as a WHILE loop. The independent and the initial iterations of monotonic dependence chains constitute the outermost parallelism. The proposed approach compares favorably with other treatments of nonuniform dependences in the literature. When there are multiple recurrence equations, a dataflow parallel execution can be scheduled using the technique to find maximum loop parallelism.
5687277
A self-adaptive scheduling algorithm of on-demand broadcasts
In mobile wireless systems data on air can be accessed by a large number of mobile users. Many of these applications such as wireless internets and traffic information systems are pull-based, that is, they respond to on-demand user requests. In this paper, we study the scheduling problems of on-demand broadcast environments. Traditionally, the response time of the requests has been used as a performance measure. In this paper we consider the performance as the average cost of request composed of three kinds of costs—access time cost, tuning time cost, and cost of handling failure request. Our main contribution is a self-adaptive scheduling algorithm named LDFC, which computes the delay cost of data item as the priority for broadcast. It performs well compared with some previous algorithms in this context.