16190492
Noise Estimation from a Single Image
In order to work well, many computer vision algorithms require that their parameters be adjusted according to the image noise level, making it an important quantity to estimate. We show how to estimate an upper bound on the noise level from a single image based on a piecewise smooth image prior model and measured CCD camera response functions. We also learn the space of noise level functions how noise level changes with respect to brightness and use Bayesian MAP inference to infer the noise level function from a single image. We illustrate the utility of this noise estimation for two algorithms: edge detection and featurepreserving smoothing through bilateral filtering. For a variety of different noise levels, we obtain good results for both these algorithms with no user-specified inputs.
41028764
Large environment rendering using plenoptic primitives
One of the most difficult tasks in computer graphics is to enable virtual walkthroughs in very large and complicated environments that are photorealistic, seamless, and in real time. Current image-based rendering techniques, while capable of photorealism and interactive speeds, have failed in practice to extend to visualizations of such environments. We demonstrate an approach that defines a virtual walkthrough experience using plenoptic primitives (PPs). A PP can be any type of local visual experience: 360/spl deg/ static panorama, panoramic video (PV), lumigraph/light field representation, or concentric mosaics (CMs). By combining them judiciously, user experience can be authored with significantly reduced effort while maintaining high-quality user experience. We illustrate our technique on synthetic and real environments using PVs and CMs and show how the problem of achieving smooth transitions among PVs and CMs can be solved by using position-dependent local geometries.
17348246
Lighting interpolation by shadow morphing using intrinsic lumigraphs
Densely-sampled image representations such as the light field or lumigraph have been effective in enabling photorealistic image synthesis. Unfortunately, lighting interpolation with such representations has not been shown to be possible without the use of accurate 3D geometry and surface reflectance properties. In this paper we propose an approach to image-based lighting interpolation that is based on estimates of geometry and shading from relatively few images. We decompose captured light fields at different lighting conditions into intrinsic images (reflectance and illumination images), and estimate view-dependent scene geometries using multi-view stereo. We call the resulting representation an intrinsic lumigraph. In the same way that the lumigraph uses geometry to permit more accurate view interpolation, the intrinsic lumigraph uses both geometry and intrinsic images to allow high-quality interpolation at different views and lighting conditions. Joint use of geometry and intrinsic images is effective in the computation of shadow masks for shadow prediction at new lighting conditions. We illustrate our approach with images of real scenes.
2096181
Video editing using figure tracking and image-based rendering
We describe a new approach to video editing based on the semi-automatic segmentation of video into multiple layers and the composition of layers using image-based rendering. Using figure tracking and background motion estimation, we can segment a moving figure and reconstruct the background. Using geometrically-correct pixel reprojection, layers can be composited on the basis of the geometry of the underlying scene and the position of a virtual camera. We have implemented a prototype editing system called SpliceWorld.
122813254
Shape Ambiguities in Structure From Motion
This paper examines the fundamental ambiguities and uncertainties inherent in recovering structure from motion. By examining the eigenvectors associated with null or small eigenvalues of the Hessian matrix, we can quantify the exact nature of these ambiguities and predict how they affect the accuracy of the reconstructed shape. Our results for orthographic cameras show that the bas-relief ambiguity is significant even with many images, unless a large amount of rotation is present. Similar results for perspective cameras suggest that three or more frames and a large amount of rotation are required for metrically accurate reconstruction.
47117010
Stylizing 2.5-D video
In recent years considerable interest has been given to non-photorealistic rendering of photographs, video, and 3D models for illustrative or artistic purposes. Conventional 2D inputs such as photographs and video are easy to create and capture, while 3D models allow for a wider variety of stylization techniques, such as cross-hatching. In this paper, we propose using video with depth information (2.5-D video) to combine the advantages of 2D and 3D input. 2.5-D video is becoming increasingly easy to capture, and with the additional depth information, stylization techniques that require shape information can be applied. However, because 2.5-D video contains only limited shape information and 3D correspondence over time is unknown, it is difficult to create temporally coherent stylized animations directly from raw 2.5-D video. In this paper, we present techniques for processing 2.5-D video to overcome these drawbacks, and demonstrate several styles that can be created using these techniques.
10010061
Energy-efficient skewed static logic design with dual Vt
In this paper, we describe skewed static logic (S/sup 2/L) with topology-dependent dual Vt which exhibits energy-efficient operation. S/sup 2/L consumes less dynamic and static power compared to Monotonic Static (MS) CMOS. Speed degradation of S/sup 2/L can be offset by the accelerator. We have designed NAND-NOR gate chains using 0.18 /spl mu/m CMOS technology and verified that S/sup 2/L reduces energy/spl times/delay over MS CMOS by 27-50%. Synthesis algorithm for S/sup 2/L developed and the experimental results show S/sup 2/L consumes 23% less power than MS CMOS with minor increase in delay.
6698506
Multi-layer active queue management and congestion control for scalable video streaming
Video streaming is becoming an increasingly important part of the present Internet. To guarantee a high-quality streaming environment to end users, many video applications require a strict form of network QoS that is not available in the present Internet. Thus, to supplement the best-effort model of existing networks, we study a new video streaming framework that allows applications to mark their own packets with different priority and use multiqueue congestion control inside routers to effectively drop the less-important packets during buffer overflows. We describe priority AQM algorithms that provide "optimal" performance to video applications under arbitrary network loss and study a variation of Kelly's congestion control in combination with our framework. We call the combined architecture PELS - partitioned enhancement layer streaming.
29231099
A new circuit optimization technique for high performance CMOS circuits
A novel transistor sizing technique with a concise problem formulation and rigorous optimization scheme is described. A circuit optimization technique for high-performance CMOS circuits is presented for proper balance of chip speed and area. The timing specification is accommodated as a design constraint, and reliability issues in the charge sharing and noise margin, which have been neglected in previous optimization tools, are also embedded into the design constraints. The optimization scheme used in this approach does not require derivatives, and therefore, can be used for a broad class of continuous cost functions. Special attention is given to the most effective use of silicon area based on the sensitivity of the delay time with respect to the transistor size. Excessively large transistor sizes are avoided by using the resource redistribution scheme. This timing allocation scheme allows the computation time to be linearly proportional to the number of gates. >
18755002
Color image decomposition and restoration
Meyer has recently introduced an image decomposition model to split an image into two components: a geometrical component and a texture (oscillatory) component. Inspired by his work, numerical models have been developed to carry out the decomposition of gray scale images. In this paper, we propose a decomposition algorithm for color images. We introduce a generalization of Meyer’s G norm to RGB vectorial color images, and use Chromaticity and Brightness color model with total variation minimization. We illustrate our approach with numerical examples.
13489029
An integrated approach to realistic worst-case design optimization of MOS analog circuits
The authors present a new integrated approach for the optimization of MOS analog circuit performance by using realistic worst-case device parameter files, each corresponding to a performance measure. Nonlinear response surfaces are constructed for the performance measures of interest, and the worst-case device parameter files are identified by solving a set of suitably cast nonlinear programming problems. The worst-case files are shown to depend on the values of the designable parameters. An efficient method of incorporating this dependence during worst-case design optimization has been developed. This method enables the design of circuits with optimal performance and high parametric yields. Some illustrative analog circuit examples are given to demonstrate the application of the worst-case design optimization procedure.<<ETX>>