5718915
Determination of motion breakpoints in a task sequence from human hand motion
This paper describes the authors' work on the temporal segmentation of grasping task sequences based on human hand motion. The segmentation process results in the identification of motion breakpoints separating the different constituent phases of the grasping task. A grasping task is composed of three basic phases: pregrasp phase, static grasp phase, and manipulation phase. The authors show that by analyzing the fingertip polygon (preshape) area and the speed of hand movement, they can divide a task into meaningful action segments such as approach object, grasp object, manipulate object, place object, and depart. The authors introduce a measure called the volume sweep rate, which is the product of the fingertip polygon area and the hand speed. The profile of this measure is also used in the determination of the task breakpoints. The temporal task segmentation process is important as it serves as a preprocessing step to the characterization of the task phases. Once the breakpoints have been identified, further analyses such as grasp recognition and object motion extraction can then be carried out.<<ETX>>
40596005
Survey of image-based representations and compression techniques
We survey the techniques for image-based rendering (IBR) and for compressing image-based representations. Unlike traditional three-dimensional (3-D) computer graphics, in which 3-D geometry of the scene is known, IBR techniques render novel views directly from input images. IBR techniques can be classified into three categories according to how much geometric information is used: rendering without geometry, rendering with implicit geometry (i.e., correspondence), and rendering with explicit geometry (either with approximate or accurate geometry). We discuss the characteristics of these categories and their representative techniques. IBR techniques demonstrate a surprising diverse range in their extent of use of images and geometry in representing 3-D scenes. We explore the issues in trading off the use of images and geometry by revisiting plenoptic-sampling analysis and the notions of view dependency and geometric proxies. Finally, we highlight compression techniques specifically designed for image-based representations. Such compression techniques are important in making IBR techniques practical.
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.
44673585
Characterization of Errors in Compositing Panoramic Images
A panoramic image has a 360° horizontal field of view, and it can provide the viewer the impression of being immersed in the scene. A panorama is created by first taking a sequence of images while rotating the camera about a vertical axis. These images are then projected onto a cylindrical surface before being seamlessly composited. The cross-sectional circumference of the cylindrical panorama is called thecompositing length. This work characterizes the error in compositing panoramic images due to errors in some of the intrinsic parameters. The intrinsic camera parameters that are considered are the camera focal length and the radial distortion coefficient. We show that the error in the compositing length is more sensitive to the error in the camera focal length. Especially important is the discovery that the relative error in compositing length is always smaller than the relative error in the focal length. This means that the error in focal length can be corrected by iteratively using the composited length to compute a new and more correct focal length. Thiscompositing approach to camera calibrationhas the advantages of not requiring both feature detection and separate prior calibration.
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.
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.
5192887
Convexity-based algorithms for design centering
A new technique for design centering and polytope approximation of the feasible region for a design are presented. In the first phase, the feasible region is approximated by a convex polytope, using a method based on a theorem on convex sets. As a natural consequence of this approach, a good approximation to the design center is obtained. In the next phase, the exact design center is estimated using one of two techniques that we present in this paper. The first inscribes the largest Hessian ellipsoid, which is known to be a good approximation to the shape of the polytope, within the polytope. This represents an improvement over previous methods, such as simplicial approximation, where a hypersphere or a crudely estimated ellipsoid is inscribed within the approximating polytope. However, when the probability density functions of the design parameters are known, the design center does not necessarily correspond to the center of the largest inscribed ellipsoid. Hence, a second technique is developed that incorporates the probability distributions of the parameters, under the assumption that their variation is modeled by Gaussian probability distributions. The problem is formulated as a convex programming problem and an efficient algorithm is used to calculate the design center, using fast and efficient Monte Carlo methods to estimate the yield gradient. An example is provided to illustrate how ellipsoid-based methods fail to incorporate the probability density functions and is solved using the convex programming-based algorithm. >
44275614
Cell-level placement for improving substrate thermal distribution
The dramatic increase of power consumption in very large scale integration circuits has led to high operating temperature and large thermal gradient, thereby resulting in serious timing and reliability concerns. Temperature-tracking is thus becoming of paramount importance in modern electronic design automation (EDA) tools. In this paper we present two thermal placement tools for standard cell and macro cell design styles respectively. They are aimed at reducing hot spots in a design without compromising traditional design metrics such as area and wire length. We developed a compact substrate thermal model that can be used by the placer to calculate the temperature profile of a placement efficiently, or to convert the user-specified temperature constraint into the corresponding power distribution constraint as an alternative placement objective. As a result, our method is much more efficient than directly employing temperature profile simulation during the placement process. The simulation results show noticeable improvement of thermal distribution over the traditional placement algorithm, with little impact on area and wire length of the final layout.
8347342
Keyword-based document clustering
Document clustering is an aggregation of related documents to a cluster based on the similarity evaluation task between documents and the representatives of clusters. Terms and their discriminating features of terms are the clue to the clustering and the discriminating features are based on the term and document frequencies. Feature selection method on the basis of frequency statistics has a limitation to the enhancement of the clustering algorithm because it does not consider the contents of the cluster objects. In this paper, we adopt a content-based analytic approach to refine the similarity computation and propose a keyword-based clustering algorithm. Experimental results show that content-based keyword weighting outperforms frequency-based weighting method.
53239407
Logic Transformation for Low Power Synthesis
In this paper we present a new approach to the problem of local logic transformation for reduction of power dissipation in logic circuits. Based on the finite-state input transition (FIT) power dissipation model, we introduce a cost function which accounts for the effects of input capacitance, input slew rate, internal parasitic capacitance of logic gates, interconnect capacitance, as well as switching power. Our approach provides an efficient way of estimating estimating the global effect of local logic transformations in logic circuits. In our approach, the FIT model for the transitive fanout cells of a locally transformed subcircuit can be reused to measure the global power dissipation by varying the input probabilities of the transitive fanout cells. Local logic transformation is carried our based on compatible sets of permissible functions (CSPF). Experimental results show that local logic transformation based on CSPF using our cost function can reduce power consumption by about 36% on average without increase in the worst-case circuit delay.
30593608
Skyeye: An Instruction Simulator with Energy Awareness
This paper presents a novel strategy aimed at modeling the instruction energy consumption of ARM microprocessors with dynamic voltage scaling (DVS) support. A novel energy estimation algorithm is designed, which can record the function calls, and generate a detailed energy profile for each function in a specific program. Some of the optimization policies for implementation are also discussed. These optimization policies reduce the workload of the energy estimators for the individual SOC systems. The prototype system, SKYEYE, can automatically detect the voltage/frequency variation activated by DVS system, and adjust the energy estimation model accordingly. The experiment results further prove the effectiveness of the algorithm.