46648388
Parallel Progressive Radiosity with Adaptive Meshing
Progressive radiosity is widely used for realistic image synthesis in computer graphics applications. High-quality image generation usually requires radiosity with adaptive patch refinement to account for global illumination effects from irregular objects whose proximity varies in a 3D space. Parallelizing such an algorithm is difficult since computation cost for each object varies from one iteration to another depending on the location of dynamically selected shooting patches. Dynamic load balancing is required but its overhead is high for distributed memory systems. This paper presents an efficient parallel algorithm for progressive radiosity, which adopts a static processor assignment strategy to take advantages of a hierarchical computation structure in this problem, minimize communication and balance dynamic load. Our experiments on a Meiko CS-2 distributed memory machine show that this algorithm has achieved good speedups for the tested cases.
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.
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.
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.
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.
13290415
Quality-Based Software Reuse
Work in software reuse focuses on reusing artifacts. In this context, finding a reusable artifact is driven by a desired functionality. This paper proposes a change to this common view. We argue that it is possible and necessary to also look at reuse from a non-functional (quality) perspective. Combining ideas from reuse, from goal-oriented requirements, from aspect-oriented programming and quality management, we obtain a goal-driven process to enable the quality-based reusability.
12275137
Dynamically Self-Organized Service Composition in Wireless Ad Hoc Networks
Service composition is a powerful tool to create new services rapidly by reusing existing ones. Previous research mainly focuses on the wired infrastructure-based environment. With the developments in mobile devices and wireless communication technology in recent years, mobile ad hoc network has received an increasing attention as a new communication paradigm. However, the existing service composition techniques do not work any longer in an ad hoc environment. In this paper, we present the service composition problem in wireless ad hoc network with full consideration of the characteristics of an ad hoc environment. To solve this problem, we develop two service composition routing algorithms, Simple Broadcasting Service Composition and Behavior Evolution Service Composition. The main contribution of our algorithms is that the whole process of service composition is done by the cooperation of nodes on-the-fly instead of a centralized broker to meet the peculiarity of ad hoc networks. Finally, we describe an initial implementation architecture for service composition in wireless ad hoc networks.
15539720
Extrapolated impulse response filter and its application in the synthesis of digital filters using the frequency-response masking technique
Techniques based on the frequency-response masking (FRM) approach are known to be highly effective for reducing the number of multipliers and adders in linear-phase finite-impulse response (FIR) filters. The basic FRM structure comprises a band-edge shaping filter and two masking filters. It is observed that the impulse response of the band-edge shaping filter of an FRM structure exhibits a quasi-periodic property. Previous study showed that lowpass or highpass digital FIR filters, whose impulse responses are quasi-periodic, can be synthesized using extrapolated impulse response technique, which leads to structure with much reduced arithmetic complexity. In this paper, an implementation of the extrapolated impulse response filter is presented. An FRM technique incorporating extrapolated impulse response band-edge shaping filter is introduced. An iterative optimization procedure is proposed to design the FRM sub-filters. It is demonstrated using an example taken from the literature that our new technique produces a saving of over 20% in the number of multipliers used. r 2004 Elsevier B.V. All rights reserved.
45980845
Optimal adaptive bandwidth monitoring for QoS based retrieval
Network aware multimedia delivery 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. We present an algorithm to determine the optimal amount of bandwidth testing, given a probabilistic confidence level for network-aware multimedia retrieval. Our implementation and experiments show that the algorithm finds out the optimal amount of bandwidth testing effectively with minimum computation overhead.
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.