6505111
Re-cinematography: Improving the camerawork of casual video
This article presents an approach to postprocessing casually captured videos to improve apparent camera movement. Re-cinematography transforms each frame of a video such that the video better follows cinematic conventions. The approach breaks a video into shorter segments. Segments of the source video where there is no intentional camera movement are made to appear as if the camera is completely static. For segments with camera motions, camera paths are keyframed automatically and interpolated with matrix logarithms to give velocity-profiled movements that appear intentional and directed. Closeups are inserted to provide compositional variety in otherwise uniform segments. The approach automatically balances the tradeoff between motion smoothness and distortion to the original imagery. Results from our prototype show improvements to poor quality home videos.
7524507
Video retargeting: automating pan and scan
When a video is displayed on a smaller display than originally intended, some of the information in the video is necessarily lost. In this paper, we introduce Video Retargeting that adapts video to better suit the target display, minimizing the important information lost. We define a framework that measures the preservation of the source material, and methods for estimating the important information in the video. Video retargeting crops each frame and scales it to fit the target display. An optimization process minimizes information loss by balancing the loss of detail due to scaling with the loss of content and composition due to cropping. The cropping window can be moved during a shot to introduce virtual pans and cuts, subject to constraints that ensure cinematic plausibility. We demonstrate results of adapting a variety of source videos to small display sizes.
8081608
An analytic model for Ge/Si core/shell nanowire MOSFETs considering drift-diffusion and ballistic transport
In this paper an analytic model for Ge/Si core/shell nanowire MOSFETs (NWFETs) is developed. First, the electrostatic potential and charge model are derived out from classical device physics. Then the drift-diffusion drain current model is obtained and verified by comparisons with the numerical simulation. The ballistic current model is obtained with the approximately described quantummechanical effect through modifying the intrinsic carrier concentration under 2-dimensional confinement. With the proposed model, the performances of Ge/Si core/shell NWFETs are analyzed and significant characteristics are demonstrated in details. The analytic model in this paper provides a framework for further developing compact models of the NWFETs with Ge/Si core/shell heterostructure for circuit design and simulation.
111120849
Generic Carrier-Based Core Model for Four-Terminal Double-Gate MOSFET Valid for Symmetric, Asymmetric, SOI, and Independent Gate Operation Modes
A generic carrier-based core model for undoped four-terminal double-gate (DG) MOSFET valid for symmetric, asymmetric, SOI, and independent gate operation modes is presented in this paper. Based on the exact solution of the 1-D Poisson's equation of a general DG-MOSFET configure, a generic drain current model is derived from Pao-Sah's double integral in terms of the carrier concentration. The model is verified by extensive comparisons with 2-D numerical simulations under different bias conditions to all four terminals. The concise mathematic formulation allows the unification various double-gate models into a carrier-based core model for compact DG-MOSFET model development.
29221183
Intelligent Crowd Simulation
Crowd simulation is a continuous challenge in computer animation. In this paper, we present an intelligent crowd simulation technique based on multiple autonomous agents. Each animated character (AC) is modeled as an autonomous agent, consisting of the perception, behavior planning and motion generation system. AC perceives the environment information, generates intentions and plans behaviors autonomously. To execute behaviors, appropriate motions are selected from the fundamental motion library (FML) and edited to create required motions. And the crowd behavior can be regarded as a combination of the individual behavior of each AC. The experiment shows the feasibility of this technique.
39158542
A New Algorithm of Gray Watermark Embedding
The problems of the digital information transmission safety, its’ copyright protection etc. are seriously increase. Digital watermark is one of the good solutions for many problems mentioned above. Generally the watermark information is a one-dimension random signal. Two-dimension gray watermark is difficult to guarantee the robustness of the information embedding. Put a new kind of discrete wavelet transform (DWT) and the singular value decompose (SVD) on two-dimension gray watermark, the watermark becomes very strong robust to the compression, noise, low pass filter, high pass filter and median filter. It is useful for the safety of digital information transmission and its copyright protection.
2442553
Adaptive spectrum-based variable bit truncation of discrete cosine transform (DCT) for energy-efficient wireless multimedia communication
This work presents a new adaptive scheme to reduce the computation energy of the discrete cosine transform (DCT) architecture for image/video coding. The scheme employs the noise masking effect of quantization and the spectral difference of the quantization factors. Spectrum-based variable bit truncation is used to allocate more energy for the computations that affect the low frequency DCT coefficients more. We propose a benchmark driven search mechanism based on energy and distortion weight to find the optimal truncation sets for different quality constraints and quantization tables. They are stored in a look-up table (LUT) for the on-line reconfiguration. Simulation results show that significant energy saving is achieved with negligible quality degradation.
45720537
Bayesian Network Structure Ensemble Learning
Bayesian networks (BNs) have been widely used for learning model structures of a domain in the area of data mining and knowledge discovery. This paper incorporates ensemble learning into BN structure learning algorithms and presents a novel ensemble BN structure learning approach. Based on the Markov condition and the faithfulness condition of BN structure learning, our ensemble approach proposes a novel sample decomposition technique and a components integration technique. The experimental results reveal that our ensemble BN structure learning approach can achieve an improved result compared with individual BN structure learning approach in terms of accuracy.
6780116
Joint MMSE Vector Precoding Based on GMD Method for MIMO Systems
We propose a geometric mean decomposition (GMD) based vector precoding (VP) for multiple input multiple output (MIMO) systems. Minimum mean square error (MMSE) criterion is used for the joint VP design. The application of GMD method eliminates the imbalance among subchannel gains and obtains a better perturbation vector than the conventional method. We then exploit the extended channel matrix for further performance improvement. Simulation results show the proposed schemes significantly outperform the existing VP schemes.
18563923
Forward and Inverse Solutions of Electrocardiography Problem Using an Adaptive BEM Method
The construction of geometry models of heart-torso is critical for solving the forward and inverse problems of magneto- and electrocardiography (MCG/ECG). Boundary element method (BEM) is a commonly used numerical approach for the solution of these problems and it requires the modeling of interfaces between various tissue regions. In this study, a new BEM (h-adaptive type) has been applied to the ECG forward/inverse problems. Compared with those traditional BEMs, the adaptive BEM can self-adjust the number and size of the boundary element (BE) meshes according to an error indicator, and thus can save a lot of computational time and also improve the accuracy of the forward and inverse solutions. In this paper, the procedure of the adaptive triangular mesh generation is detailed and the algorithm is tested using a concentric sphere model and a realistic heart-torso model. For the realistic torso model, to improve the numerical accuracy, a number of new nodes are added on the basis of initial torso BE meshes, and the corresponding node coordinates are determined using an approach called Parametric Fourier Representation (PFR) of closed polygons. The simulation results show that the adaptive BEM is more accurate and efficient than traditional BEMs and therefore it is a very promising numerical scheme for ECG forward/inverse problems.
42610771
A Novel Ordering-Based Greedy Bayesian Network Learning Algorithm on Limited Data