7282879
Jump flooding in GPU with applications to Voronoi diagram and distance transform
This paper studies jump flooding as an algorithmic paradigm in the general purpose computation with GPU. As an example application of jump flooding, the paper discusses a constant time algorithm on GPU to compute an approximation to the Voronoi diagram of a given set of seeds in a 2D grid. The errors due to the differences between the approximation and the actual Voronoi diagram are hardly noticeable to the naked eye in all our experiments. The same approach can also compute in constant time an approximation to the distance transform of a set of seeds in a 2D grid. In practice, such constant time algorithm is useful to many interactive applications involving, for example, rendering and image processing. Besides the experimental evidences, this paper also confirms quantitatively the effectiveness of jump flooding by analyzing the occurrences of errors. The analysis is a showcase of insights to the jump flooding paradigm, and may be of independent interests to other applications of jump flooding.
14857874
Anti-aliasing and Continuity with Trapezoidal Shadow Maps
This paper proposes a new shadow map technique termed trapezoidal shadow maps to calculate high quality shadows in real-time applications. To address the resolution problem of the standard shadow map approach, our technique approximates the eye's frustum as seen from the light with a trapezoid to warp it onto a shadow map. Such a trapezoidal approximation, which may first seem straightforward, is carefully designed to achieve the goal of good shadow quality for objects from near to far, and to address the continuity problem that is found in all existing shadow map approaches. The continuity problem occurs mainly when the shadow map quality changes significantly from frame to frame due to the motion of the eye or the light. This results in flickering of shadows. On the whole, our proposed approach is simple to implement without using complex data structures and it maps well to graphics hardware as shown in our experiments with large virtual scenes of hundreds of thousands to over a million of triangles.
7171205
An optimal bound for high-quality conforming triangulations
AbstractThis paper shows that, for any plane geometric graph
$$\mathcal{G}$$
 withn vertices, there is a triangulation
$$\mathcal{T}$$
 that conforms to
$$\mathcal{G}$$
, i.e., each edge of
$$\mathcal{G}$$
 is the union of some edges of
$$\mathcal{T}$$
, where
$$\mathcal{T}$$
 hasO(n2) vertices with each angle of its triangles measuring no more than 11/15π. Additionally,
$$\mathcal{T}$$
 can be computed inO(n2 logn) time.
15339123
Utilizing jump flooding in image-based soft shadows
This paper studies the usage of the GPU as a collection of groups of related processing units, where each group communicates in some way to complete a computation efficiently and effectively. In particular, we use the GPU to perform jump flooding to pass information among groups of processing units in the design of two simple real-time soft shadow algorithms. These two algorithms are purely image-based in generating plausible soft shadows. Their computational costs depend mainly on the resolution of the shadow map or the screen. They run on an order of magnitude faster than existing comparable methods.
2598412
Embedded operating system energy analysis and macro-modeling
A large and increasing number of modern embedded systems are subject to tight power/energy constraints. It has been demonstrated that the operating system (OS) can have a significant impact on the energy efficiency of the embedded system. Hence, analysis of the energy effects of the OS is of great importance. Conventional approaches to energy analysis of the OS (and embedded software, in general) require the application software to be completely developed and integrated with the system software, and that either measurement on a hardware prototype or detailed simulation of the entire system be performed. Since this process requires significant design effort, unfortunately, it is typically too late in the design cycle to perform high-level or architectural optimizations on the embedded software, restricting the scope of power savings. Our work recognizes the need to provide embedded software designers with feedback about the effect of different OS services on energy consumption early in the design cycle. As a first step in that direction, this paper presents a systematic methodology to perform energy analysis and macro-modeling of an embedded OS. Our energy macro-models provide software architects and developers with an intuitive model for the OS energy effects, since they directly associate energy consumption with OS services and primitives that are visible to the application software. Our methodology consists of (i) an analysis stage, where we identify a set of energy components, called energy characteristics, which are useful to the designer in making OS-related design trade-offs, and (ii) a subsequent macromodeling stage, where we collect data for the identified energy components and automatically derive macro-models for them. We validate our methodology by deriving energy macro-models for two state-of-the-art embedded OS's, /spl mu/C/OS and Linux OS.
11321791
A new face detection method based on shape information
Automatic detection of human faces is one of the most difficult problems in pattern recognition. In many practical applications (e.g. personal identification using photo-IDs), face images often have a simple background. In this paper, we propose a new method based on shape information. Our system can be very efficient for images with simple background. Input image is first enhanced by means of histogram equalization, followed by edge detection based on a multiple-scale filter. The extracted edges are then linked using a method based on an energy function. The face contour is finally extracted using the direction information of the linked edges. Experimental results are included to verify the effectiveness of this method. (C) 2000 Elsevier Science B.V. All rights reserved.
8559676
A simulation framework for energy-consumption analysis of OS-driven embedded applications
Energy consumption has become a major focus in the design of embedded systems (e.g., mobile computing and wireless communication devices). In particular, a shift of emphasis from hardware-oriented low-energy design techniques to energy-efficient embedded software design has occurred progressively in the past few years. To that end, various techniques have been developed for the design of energy-efficient embedded software. In operating system (OS)-driven embedded systems, the OS has a significant impact on the system's energy consumption directly (energy consumption associated with the execution of the OS functions and services), as well as indirectly (interaction of the OS with the application software). As a first step toward designing energy-efficient OS-based embedded systems, it is important to analyze the energy consumption of embedded software by taking the OS energy characteristics into account. To facilitate such studies, we present, in this work, an energy simulation framework that can be used to analyze the energy consumption characteristics of an embedded system featuring the embedded Linux OS running on the StrongARM processor. The framework allows software designers to study the energy consumption of the system software in relation to the application software, identify the energy hot spots, and perform design changes based on the knowledge of the OS energy consumption characteristics as well as application-OS interactions.
2166869
Font recognition based on global texture analysis
In this paper, we describe a new texture analysis based approach towards font recognition. Existing methods are typically based on local features that often require connected components analysis. In our new method, we take the document as an image containing some special textures, and font recognition as texture identification. The method is content independent and involves no local feature analysis. Global features are extracted by texture analysis. We apply the well-established 2D Gabor filtering technique to extract such features and a weighted Euclidean distance classifier to fulfil the recognition task. Experiments are made using 6,000 samples of 24 frequently used Chinese fonts (6 typefaces combined with 4 styles) and very promising results are achieved.
17392876
High-level software energy macro-modeling
This paper presents an efficient and accurate high-level software energy estimation methodology using the concept of characterization-based macro-modeling. In characterization-based macro-modeling, a function or sub-routine is characterized using an accurate lower-level energy model of the target processor, to construct a macro-model that relates the energy consumed in the function under consideration to various parameters that can be easily observed or calculated from a high-level programming language description. The constructed macro-models eliminate the need for significantly slower instruction-level interpretation or hardware simulation that is required in conventional approaches to software energy estimation. We present two different approaches to macro-modeling for embedded software that offer distinct efficiency-accuracy characteristics: (i) complexity-based macro-modeling, where the variables that determine the algorithmic complexity of the function under consideration are used as macro-modeling parameters, and (ii) profiling-based macro-modeling, where internal profiling statistics for the functions are used as parameters in the energy macro-models. We have experimentally validated our software energy macro-modeling techniques on a wide range of embedded software routines and two different target processor architectures. Our experiments demonstrate that high-level macro-models constructed using the proposed techniques are able to estimate the energy consumption to within 95% accuracy on the average, while commanding speedups of one to five orders-of-magnitude over current instruction-level and architectural energy estimation techniques.