37555026
Incomplete motion feature tracking algorithm in video sequences
To effectively track incomplete motion features, a novel feature tracking algorithm for motion capture is presented. According to feature attributes and relationship among features, extracted features are classified as four types of features. Then different strategies are applied to track different kinds of features. To verify the tracks, cross correlation test and predicted 3D model based test are used to test and remove outliers. Experimental results demonstrate the effectiveness of our algorithm.
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.
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.
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.
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.
950378
Extending OpenMP for heterogeneous chip multiprocessors
The emergence of system-on-chip (SOC) design shows the growing popularity of the integration of multiple-processors into one chip. We propose that high-level abstraction of parallel programming like OpenMP is suitable for chip multiprocessors. For SOCs, the heterogeneity exists within one chip such that it may have different types of multiprocessors, e.g. RISC-like processors or DSP-like processors. Incorporating different processors into OpenMP is challenging. We present our solutions to extend OpenMP directives to tackle this heterogeneity. Several optimization techniques are proposed to utilize advanced architecture features of our target SOC, the software scalable system on chip (3SoC). Preliminary performance evaluation shows scalable speedup using different types of processors and performance improvement through individual optimization.
35354920
Color text image binarization based on binary texture analysis
In this paper, a novel binarization algorithm for color text images is presented. This algorithm effectively integrates color clustering and binary texture analysis, and is capable of handling situations with complex backgrounds. In this algorithm, dimensionality reduction and graph theoretical clustering are first employed. As the result, binary images related to clusters can be obtained. Binary texture analysis is then performed on each candidate binary image. Two kinds of effective texture features, run-length histogram and spatial-size distribution related respectively, are extracted and explored. Cooperating with an LDA classifier, the optimal candidate of the best binarization effect is obtained. Experiments with images collected from Internet has been carried out and compared with existing techniques, both show the effectiveness of the algorithm.
14601627
Semantic Modeling and Design Patterns for Asynchronous Events in Web Service Interaction
This paper proposes a conceptual model for modeling static and dynamic event sources by reusing the information in WSDL. A set-theoretic semantics for event subscription is introduced, based on which two metrics, recall and precision, are proposed to measure the accuracy of event subscriptions. We discuss the accuracy of several event subscription strategies under the framework of Web service event subscription standard proposals (WS-Eventing and WS-Notification). Four major types of event broker design patterns are discussed based on two visibility/reachability factors: if sink knows the source and if source can deliver events directly to the sink. The implication on the broker state and message routing is studied in this analysis. A prototype implementation indicated that these design patterns are feasible
3230690
A new verification-based fast-match for large vocabulary continuous speech recognition
Acoustic fast-match is a popular way to accelerate the search in large-vocabulary continuous-speech recognition, where an efficient method is used to identify poorly scoring phonemes and discard them from detailed evaluation. In this paper we view acoustic fast-match as a verification problem, and hence develop an efficient likelihood ratio test, similar to other verification scenarios, to perform the fast match. Various aspects of the test like the design of alternate hypothesis models and the setting of phoneme look-ahead durations and decision thresholds are studied, resulting in an efficient implementation. The proposed fast-match is tested in a large vocabulary speech recognition task and it is demonstrated that depending on the decision threshold, it leads to 20-30% improvement in speed without any loss in recognition accuracy. In addition, it significantly outperforms a similar test based on using likelihoods only, which fails, in our setting, to bring any improvement in speed-accuracy trade-off. In a larger set of experiments with varying acoustic and task conditions, similar improvements are observed for the fast-match with the same model and setting. This indicates the robustness of the proposed technique. The gains due to the proposed method are obtained within a highly efficient 2-pass search strategy and similar or even higher gains are expected in other alternative search architectures.
29468800
SceBoost Learning Algorithm for Feature Selection
This paper proposes an improved boost learning algorithm, the SceBoost algorithm, and its application in developing fast and robust features for citrus canker detection by machine vision. The algorithm use symmetric cross entropy to eliminate redundancy among selected features using AdaBoost algorithm. Selected features are subjected to recognize citrus canker symptoms on given pictures of citrus foliage. Compared with related feature selection algorithm our method can get improvements in classification accuracy and significantly reduce computation time when reach the same requirements.