864760
Bayesian Tensor Inference for Sketch-Based Facial Photo Hallucination
This paper develops a statistical inference approach, Bayesian Tensor Inference, for style transformation between photo images and sketch images of human faces. Motivated by the rationale that image appearance is determined by two cooperative factors: image content and image style, we first model the interaction between these factors through learning a patch-based tensor model. Second, by introducing a common variation space, we capture the inherent connection between photo patch space and sketch patch space, thus building bidirectional mapping/inferring between the two spaces. Subsequently, we formulate a Bayesian approach accounting for the statistical inference from sketches to their corresponding photos in terms of the learned tensor model. Comparative experiments are conducted to contrast the proposed method with state-of-the-art algorithms for facial sketch synthesis in a novel face hallucination scenario: sketch-based facial photo hallucination. The encouraging results obtained convincingly validate the effectiveness of our method.
9354577
Identifying Faces in a 2D Line Drawing Representing a Manifold Object
A straightforward way to illustrate a 3D model is to use a line drawing. Faces in a 2D line drawing provide important information for reconstructing its 3D geometry. Manifold objects belong to a class of common solids and most solid systems are based on manifold geometry. In this paper, a new method is proposed for finding faces from single 2D line drawings representing manifolds. The face identification is formulated based on a property of manifolds: each edge of a manifold is shared exactly by two faces. The two main steps in our method are (1) searching for cycles from a line drawing and (2) searching for faces from the cycles. In order to speed up the face identification procedure, a number of properties, most of which relate to planar manifold geometry in line drawings, are presented to identify most of the cycles that are or are not real faces in a drawing, thus reducing the number of unknown cycles in the second searching. Schemes to deal with manifolds with curved faces and manifolds each represented by two or more disjoint graphs are also proposed. The experimental results show that our method can handle manifolds previous methods can handle, as well as those they cannot.
2027823
Evolutionary Search for Faces from Line Drawings
Single 2D line drawing is a straightforward method to illustrate 3D objects. The faces of an object depicted by a line drawing give very useful information for the reconstruction of its 3D geometry. Two recently proposed methods for face identification from line drawings are based on two steps: finding a set of circuits that may be faces and searching for real faces from the set according to some criteria. The two steps, however, involve two combinatorial problems. The number of the circuits generated in the first step grows exponentially with the number of edges of a line drawing. These circuits are then used as the input to the second combinatorial search step. When dealing with objects having more faces, the combinatorial explosion prevents these methods from finding solutions within feasible time. This paper proposes a new method to tackle the face identification problem by a variable-length genetic algorithm with a novel heuristic and geometric constraints incorporated for local search. The hybrid GA solves the two combinatorial problems simultaneously. Experimental results show that our algorithm can find the faces of a line drawing having more than 30 faces much more efficiently. In addition, simulated annealing for solving the face identification problem is also implemented for comparison.
6371621
3D object reconstruction from a single 2D line drawing without hidden lines
The human vision system can interpret a single 2D line drawing as a 3D object without much difficulty even if the hidden lines of the object are invisible. Several reconstruction approaches have tried to emulate this ability, but they cannot recover the complete object if the hidden lines of the object are not shown. This paper proposes a novel approach for reconstructing complete 3D objects from line drawings without hidden lines. First, we develop some constraints and properties for the inference of the topology of the invisible edges and vertices of an object. Then we present a reconstruction method based on perceptual symmetry and planarity of the object. We give a number of examples to demonstrate the ability of our approach.
13586161
Shape from regularities for interactive 3D reconstruction of piecewise planar objects from single images
3D object reconstruction from single 2D images has many applications in multimedia. This paper proposes an approach based on image regularities such as connectivity, parallelism, and orthogonality possessed by the objects with simple user interactions. It is assumed that the objects are piecewise planar. By representing the 3D objects as a shape vector consisting of the normals of the faces of the objects, we impose geometric constraints on this shape vector using the regularities of the objects. We derive a system of equations in terms of the shape vector and the focal length, which we can solve for the shape vector optimally. Experimental results on real images are shown to demonstrate the effectiveness of this method.
16633922
Detecting irregularity in videos using kernel estimation and KD trees
Automatic event understanding is the ultimate goal for many visual surveillance systems. In this paper, we propose a novel approach for on-line detecting unusual human activities in videos without the need to explicitly define all valid configurations. Within the framework of Bayesian inference, the detection process is formulated as an MAP estimation where we attempt to find whether activities in new video segments have similar activities in a video database. Our approach has three contributions: firstly, we build the statistical representation of normal behaviors in the database using nonparametric kernel density estimation; secondly, local feature descriptors are highly compressed using PCA and stored in a K-D tree structure, making the search for behavior-based similarity fast and effective; thirdly, the K-D trees are used to generate multiple hypotheses which compete for the optimal classification. The approach requires no tracking, no explicit motion estimation, and no predefined class-based templates. Experimental results have validated our approach in many real-world video sequences.
13217169
New Method for Constructing Isospectral Graphs
There exist several methods available to construct isospectral molecular graphs.l-1° Recently, M. RandiC and his co-workers proposed the ring enlargement process (vide infra) for constructing subspectral graphs.” This method can be also used to construct isospectral graphs; however, it may fail sometimes. For example, the isospectral pair 1, 2 can be enlarged to the isospectral graphs 3,4 shown in Figure 1, where the symbol ‘‘z” signifies an isospectral pair and “-” denotes the ring enlargement procedure. Eigenvalues of 3, 4 are divided into two parts, those in coincidence with that of 1 , 2 are listed on the left, and the remaining ones are put on the right. On the other hand, graph pairs 7, 8 and 9, 10 in Figure 2, yielded from isospectral pair 5, 6, are not isospectral. Noticing the difference of the spectrum of graphs XX, XX’ (by “XX, XX”’ we mean that they are generated from subgraph X in double size by the enlargement procedure, such as 7, 8 from 5; and 9, 10 from a), RandiC suggested that if XX, XX’ are bipartite, they should be isospectral, because all eigenvalues now occur in pairs and the difference between XX and XX’ disappears. Hence, he proposed a conjecture below. CONJECTURE: If graph X yields nonisomorphic bipartite enlargements XX, XX’, etc.; the derived graphs are not only superspectral to the parent graph X but are also mutually cospectral.
8458381
Dynamic Resource Selection For Service Composition in The Grid
While numerous efforts have focused on service composition in the Grid environment, service selection among similar services from multiple providers has not been addressed. In particular, all service composition work done so far are based on a given selection of services under a well set environment. As a result, uncertainty (e.g., server load, network traffic, computation time of the services due to changing memory and other unexpected conditions) under a real, dynamic environment has never been considered. This paper prototypes the service selection under a Grid environment and proposes an uncertainty framework to address the issue. Experimental results show that our considerations are valid and our preliminary solution works well in our Globus Grid network.
2599117
Composite Synchronization in Parallel Discrete-Event Simulation
This paper considers a technique for composing global (barrier-style) and local (channel scanning) synchronization protocols within a single parallel discrete-event simulation. Composition is attractive because it allows one to tailor the synchronization mechanism to the model being simulated. We first motivate the problem by showing the large performance gap that can be introduced by a mismatch of model and synchronization method. Our solution calls for each channel between submodels to be classified as synchronous or asynchronous. We mathematically formulate the problem of optimally classifying channels and show that, in principle, the optimal classification can be obtained in time proportional to max{C/spl times/log C, V/spl times/N}, where C is the number of channels, V the number of unique minimal delays on those channels, and N is the number of submodels. We then demonstrate an implementation which finds an optimal solution at runtime and consider its performance on network topologies, including one of the global Internet at the autonomous system level. We find that the automated method effectively determines channel assignments that maximize performance.
20735579
Kinetically stable task assignment for networks of microservers
• Job titles for all employees • Most recent payroll data (wages, hours, job codes, and dates of hire) • Union contracts • Employee handbooks or benefit descriptions • Summary plan descriptions for health and retirement plans • Benefit costs summaries or insurance bills For a detailed listing of information that BLS economists typically request, please visit the National Compensation Survey Web site at http://www.bls.gov/ncs/collection.htm. What is the National Compensation Survey (NCS)?
8844798
Learning not to share
Strong reasons exist for executing a large-scale discrete-event simulation on a cluster of processor nodes (each of which may be a shared-memory multiprocessor or a uniprocessor). This is the architecture of the largest scale parallel machines, and so the largest simulation problems can only be solved this way. It is a common architecture even in less esoteric settings, and is suitable for memory-bound simulations. This paper describes our approach to porting the SSF simulation kernel to this architecture, using the Message Passing Interface (MPI) system. The notable feature of this transformation is to support an efficient two-level synchronization and communication scheme that addresses cost discrepancies between shared-memory and distributed memory. In the initial implementation, we use a globally synchronous approach between distributed-memory nodes, and an asynchronous shared-memory approach within a SMP cluster. The SSF API reflects inherently shared-memory assumptions; we report therefore on our approach for porting an SSF kernel to a cluster of SMP nodes. Experimental results on two architectures are described, for a model of TCP/IP traffic flows over a hierarchical network. The performance on a distributed network of commodity SMPs connected through ethernet is seen to frequently exceed performance on a Sun shared-memory multiprocessor.