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.
207155902
Controllable smoke animation with guiding objects
This article addresses the problem of controlling the density and dynamics of smoke (a gas phenomenon) so that the synthetic appearance of the smoke (gas) resembles a still or moving object. Both the smoke region and the target object are represented as implicit functions. As a part of the target implicit function, a shape transformation is generated between an initial smoke region and the target object. In order to match the smoke surface with the target surface, we impose carefully designed velocity constraints on the smoke boundary during a dynamic fluid simulation. The velocity constraints are derived from an iterative functional minimization procedure for shape matching. The dynamics of the smoke is formulated using a novel compressible fluid model which can effectively absorb the discontinuities in the velocity field caused by imposed velocity constraints while reproducing realistic smoke appearances. As a result, a smoke region can evolve into a regular object and follow the motion of the object, while maintaining its smoke appearance.
28175373
Mesh editing with poisson-based gradient field manipulation
In this paper, we introduce a novel approach to mesh editing with the Poisson equation as the theoretical foundation. The most distinctive feature of this approach is that it modifies the original mesh geometry implicitly through gradient field manipulation. Our approach can produce desirable and pleasing results for both global and local editing operations, such as deformation, object merging, and smoothing. With the help from a few novel interactive tools, these operations can be performed conveniently with a small amount of user interaction. Our technique has three key components, a basic mesh solver based on the Poisson equation, a gradient field manipulation scheme using local transforms, and a generalized boundary condition representation based on local frames. Experimental results indicate that our framework can outperform previous related mesh editing techniques.
11797790
Two-Level Image Segmentation Based on Region and Edge Integration
This paper introduces a two-level approach for image seg- mentation based on region and edge integration. Edges are first detected in the original image using a combination of operators for intensity gra- dient and texture discontinuities. To preserve the spatial coherence of the edges and their surrounding image regions, the detected edges are vectorized into connected line segments which serve as the basis for a constrained Delaunay triangulation. Segmentation is first performed on the triangulation using graph cuts. Our method favors segmentations that pass through more vectorized line segments. Finally, the obtained segmentation on the triangulation is projected onto the original image and region boundaries are refined to achieve pixel accuracy. Experimen- tal results show that the two-level approach can achieve accurate edge localization, better spatial coherence and improved efficiency.
3019671
Extracting Objects from Range and Radiance Images
In this paper, we present a pipeline and several key techniques necessary for editing a real scene captured with both cameras and laser range scanners. We develop automatic algorithms to segment the geometry from range images into distinct surfaces, register texture from radiance images with the geometry, and synthesize compact high-quality texture maps. The result is an object-level representation of the scene which can be rendered with modifications to structure via traditional rendering methods. The segmentation algorithm for geometry operates directly on the point cloud from multiple registered 3D range images instead of a reconstructed mesh. It is a top-down algorithm which recursively partitions a point set into two subsets using a pairwise similarity measure. The result is a binary tree with individual surfaces as leaves. Our image registration technique performs a very efficient search to automatically find the camera poses for arbitrary position and orientation relative to the geometry. Thus, we can take photographs from any location without precalibration between the scanner and the camera. The algorithms have been applied to large-scale real data. We demonstrate our ability to edit a captured scene by moving, inserting, and deleting objects.
1372639
Motion Field Estimation for Temporal Textures
This paper presents a novel approach for estimating the flow fields of dynamic temporal textures whose motion differs radically from that of rigid bod- ies. Our approach is based on a local flow probability distribution function at each pixel using the STAR model and the data from a spatio-temporal neighborhood. The peak of this density function can be regarded as the estimated local flow vec- tor. Our complete algorithm exploits a two-stage process. The first stage of the algorithm applies a simple tensor method to estimate the direction of the optical flow at each pixel in the texture. In the second stage, the flow probability function is used to perform a one-dimensional search along the flow direction to obtain the magnitude. Performance analysis and experiments with real video sequences show that our methods can successfully estimate flow fields.
10085601
Considering circuit observability don't cares in CNF satisfiability
Boolean satisfiability (SAT) has seen significant use in various tasks in circuit verification. A key contributor to the efficiency of contemporary SAT solvers is fast deduction using Boolean constraint propagation (BCP). This can be efficiently implemented with a conjunctive normal form (CNF) representation of a circuit. However, most circuit verification tasks start from a logic circuit description of the problem instance. A simple conversion from a logic circuit to a CNF (Tseitin, G.S., 1968), that enables the use of the CNF representation even for circuit verification tasks, loses some information regarding the structure of the circuit. One example of such structural information is circuit observability don't cares. Several recent papers have addressed the issue of handling circuit unobservability in CNF-based SAT, but none of them accurately captures the conditions for use of this information in all stages of a CNF-based SAT solver. To take such don't care information into consideration in a CNF-based SAT solver, we propose a broader approach that adds certain don't care literals to clauses in the CNF representation. These literals are treated differently at different times during the solution process, much like don't cares in logic synthesis. The major merit of this scheme is that the solver can continue to use this don't care information during the learning process, which is an important part of contemporary SAT solvers. We have implemented this approach in the zChaff SAT solver and experiments show that significant performance gain can be obtained.
8525620
Failure insensitive routing for ensuring service availability
Intra-domain routing protocols employed in the Internet route around failed links by having routers detect adjacent link failures, exchange link state changes, and recompute their routing tables. Due to several delays in detection, propagation and recomputation, it may take tens of seconds to minutes after a link failure to resume forwarding of packets to the affected destinations. This discontinuity in destination reachability adversely affects the quality of continuous media applications such as Voice over IP. Moreover, the resulting service unavailability for even a short duration could be catastrophic in the world of e-commerce. Though careful tuning of the various parameters of the routing protocols can accelerate convergence, it may cause instability when the majority of the failures are transient. To improve the failure resiliency without jeopardizing the routing stability, we propose a local rerouting based approach called failure insensitive routing. Under this approach, upon a link failure, adjacent router suppresses global updating and instead initiates local rerouting. All other routers infer potential link failures from the packet's incoming interface, precompute interface specific forwarding We demonstrate that the proposed approach provides higher service availability than the existing routing schemes.
7801331
FPGA implementation of digital filters synthesized using the frequency-response masking technique
The effective length of a filter designed using the frequency-response masking technique is very high and requires a very large number of delay elements. In this paper, we present some useful techniques for reducing the data transfer between the FPGA and external memory when the random logic are implemented using FPGA and the delay elements are implemented using external memory such as DRAM.
13911639
A Cost-Efficient 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 including 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 of broadcast. It costs less compared with some previous algorithms in this context, and shows good adaptability as well even in pure push-based broadcasts.
11507388
JPT: A Java Parallelization Tool
PVM is a succesfull programming environment for distributed computing in the languages C and Fortran. Recently several implementations of PVM for Java have been added, making PVM programming accessible to the Java community. 
 
With PVM for Java however, the user still needs to partition the problem, calculate the data partitioning and program the message passing and synchronization. In this paper, JPT is introduced, a parallelization tool which generates PVM code from a serial Java program. JPT automatically detects parallel loops and generates master and slave PVM programs.