4908568
Insignificant shadow detection for video segmentation
To prevent moving cast shadows from being misunderstood as part of moving objects in change detection based video segmentation, this paper proposes a novel approach to the cast shadow detection based on the edge and region information in multiple frames. First, an initial change detection mask containing moving objects and cast shadows is obtained. Then a Canny edge map is generated. After that, the shadow region is detected and removed through multiframe integration, edge matching, and region growing. Finally, a post processing procedure is used to eliminate noise and tune the boundaries of the objects. Our approach can be used for video segmentation in indoor environment. The experimental results demonstrate its good performance.
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.
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.
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.
9841055
3D object retrieval using 2D line drawing and graph based relevance reedback
This paper aims to provide a user-friendly interface for 3D object retrieval. In previous 3D retrieval systems, the user mainly uses two methods to input a query: providing an existing 3D objects, or providing partial shape information of desired objects such as text and 2D shapes. The first method fails when the user does not have a similar 3D object in hand, and the second method cannot sufficiently describe 3D shapes of objects. We believe that the best way is to have a good interface that can convert a 2D sketch drawn by the user into a 3D object as the query. A 2D line drawing is easy to be drawn and is the simplest and most direct way of illustrating a 3D object. In this paper, we develop an interface of 3D object reconstruction from line drawings, which allows the user to draw line drawings of objects with both planar and curved surfaces. In addition, in order to refine the retrieved results, we develop a relevance feedback algorithm based on a novel graph discriminant analysis. Compared with recently published relevance feedback algorithms, our algorithm achieves better retrieval performance.
43415133
The performance advantage of applying compression to the memory system
The memory system stores information comprising primarily instructions and data and secondarily address information, such as cache tag fields. It interacts with the processor by supporting related traffic (again comprising addresses, instructions, and data). Continuing exponential growth in processor performance, combined with technology, architecture, and application trends, place enormous demands on the memory system to permit this information storage and exchange at a high-enough performance (i.e., to provide low latency and high bandwidth access to large amounts of information). This paper comprehensively analyzes the redundancy in the information (addresses, instructions, and data) stored and exchanged between the processor and the memory system and evaluates the potential of compression in improving performance of the memory system. Analysis of traces obtained with Sun Microsystems' Shade simulator simulating SPARC executables of nine integer and six floating-point programs in the SPEC CPU2000 benchmark suite yield impressive results. Well-designed compression schemes may provide benefits in performance that far outweigh the extra time and logic for compression and decompression. This will be more so in the future since the speed and size of logic (which will be used to perform compression/decompression) are improving and are projected to improve at a much higher rate compared to those of interconnect (which will be used to communicate the information), both on-chip and off-chip.
5682640
A dual-space approach to tracking and sensor management in wireless sensor networks
Wireless ad hoc sensor networks have the advantage of spanning a large geographical region and being able to collaboratively detect and track non-local spatio-temporal events. This paper presents a dual-space approach to event tracking and sensor resource management in sensor networks. The dual-space transformation maps a non-local phenomenon, e.g., the edge of a half-plane shadow, to a single point in the dual space, and maps locations of distributed sensor nodes to a set of lines that partitions the dual space. The detection problem becomes finding and tracking the cell that contains the point in the arrangement defined by these lines. This mechanism can be effectively used for power management of the sensor network - nodes that will not be immediately visited by an event can be turned off to save energy required for sensing, processing, and communication. The approach has been successfully demonstrated on a laboratory testbed built using the UC Berkeley motes sensors. An implemented application of detecting and tracking light shadow edges moving over a sensor field is described.
986436
Convergence of gauge method for incompressible flow
A new formulation, a gauge formulation of the incompressible Navier-Stokes equations in terms of an auxiliary field a and a gauge variable Φ, u = a + ⊇Φ, was proposed recently by E and Liu. This paper provides a theoretical analysis of their formulation and verifies the computational advantages. We discuss the implicit gauge method, which uses backward Euler or Crank-Nicolson in time discretization. However, the boundary conditions for the auxiliary field a are implemented explicitly (vertical extrapolation). The resulting momentum equation is decoupled from the kinematic equation, and the computational cost is reduced to solving a standard heat and Poisson equation. Moreover, such explicit boundary conditions for the auxiliary field a will be shown to be unconditionally stable for Stokes equations. For the full nonlinear Navier-Stokes equations the time stepping constraint is reduced to the standard CFL constraint Δt/Δx < C. We also prove first order convergence of the gauge method when we use MAC grids as our spatial discretization. The optimal error estimate for the velocity field is also obtained.
18277516
Mesh Optimisation Using Edge Information in Feature-Based Surface Reconstruction
One of the most challenging and fundamental problems in computer vision is to reconstruct a surface model given a set of uncalibrated 2D images. Well-established Structure from Motion (SfM) algorithms often result in a sparse set of 3D surface points, but surface modelling based on sparse 3D points is not easy. In this paper, we present a new method to refine and optimise surface meshes using edge information in the 2D images. We design a meshing – edge point detection – re-meshing scheme that can gradually refine the surface mesh until it best fits the true physical surface of the object being modelled. Our method is tested on real images and satisfactory results are obtained.
894781
A constraint-based application model and scheduling techniques for power-aware systems
New embedded systems must be power-aware, not just low-power. That is, they must track their power sources and the changing power and performance constraints imposed by the environment. Moreover, they must fully explore and integrate many novel power management techniques. Unfortunately, these techniques are often incompatible with each other due to overspecialized formulations or they fail to consider system-wide issues. This paper proposes a new graph-based model to integrate novel power management techniques and facilitate design-space exploration of power-aware embedded systems. It captures min/max timing and min/max power constraints on computation and non-computation tasks through a new constraint classification and enables derivation of flexible system-level schedules. We demonstrate the effectiveness of this model with a power-aware scheduler on real mission-critical applications. Experimental results show that our automated techniques can improve performance and reduce energy cost simultaneously. The application model and scheduling tool presented in this paper form the basis of the IMPACCT system-level framework that will enable designers to aggressively explore many power-performance trade-offs with confidence.