13444952
Expressive speech-driven facial animation
Speech-driven facial motion synthesis is a well explored research topic. However, little has been done to model expressive visual behavior during speech. We address this issue using a machine learning approach that relies on a database of speech-related high-fidelity facial motions. From this training set, we derive a generative model of expressive facial motion that incorporates emotion control, while maintaining accurate lip-synching. The emotional content of the input speech can be manually specified by the user or automatically extracted from the audio signal using a Support Vector Machine classifier.
6260783
Style components
We propose a novel method for interactive editing of motion data based on motion decomposition. Our method employs Independent Component Analysis (ICA) to separate motion data into visually meaningful components called style components. The user then interactively identifies suitable style components and manipulates them based on a proposed set of operations. In particular, the user can transfer style components from one motion to another in order to create new motions that retain desirable aspects of the style and expressiveness of the original motion. For example, a clumsy walking motion can be decomposed so as to separate the clumsy nature of the motion from the underlying walking pattern. The clumsy style component can then be applied to a running motion, which will then yield a clumsy-looking running motion. Our approach is simple, efficient and intuitive since the components are themselves motion data. We demonstrate that the proposed method can serve as an effective tool for interactive motion analysis and editing.
2266938
Cooperative Mobile Robotics: Antecedents and Directions
There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting cooperative behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of cooperative robotics have been reported, and supporting theory is still in its formative stages. In this paper, we give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. We describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations.
19011643
Total-Order Planning with Partially Ordered Subtasks
One of the more controversial recent planning algorithms is the SHOP algorithm, an HTN planning algorithm that plans for tasks in the same order that they are to be executed. SHOP can use domaindependent knowledge to generate plans very quickly, but it can be difficult to write good knowledge bases for SHOP. 
 
Our hypothesis is that this difficulty is because SHOP's total-ordering requirement for the subtasks of its methods is more restrictive than it needs to be. To examine this hypothesis, we have developed a new HTN planning algorithm called SHOP2. Like SHOP, SHOP2 is sound and complete, and it constructs plans in the same order that they will later be executed. But unlike SHOP, SHOP2 allows the subtasks of each method to be partially ordered. 
 
Our experimental results suggest that in some problem domains, the difficulty of writing SHOP knowledge bases derives from SHOP's total-ordering requirement--and that in such cases, SHOP2 can plan as efficiently as SHOP using knowledge bases simpler than those needed by SHOP.
1446657
Fast Statistical Circuit Analysis with Finite-Point Based Transistor Model
A new approach of transistor modeling is developed for fast statistical circuit simulation in the presence of variations. For both I-V and C-V characteristics of a transistor, finite data points are identified by their physical meaning; the impact of process and design variations is embedded into these points as closed-form expressions. Then, the entire I-V and C-V are extrapolated using polynomial formulas. This novel approach significantly enhances the simulation speed with sufficient accuracy. The model is implemented in Verilog-A at 65nm node. Compared to simulations with the BSIM model, the computation time can be reduced by 7times in transient analysis and 9times in Monte-Carlo simulations
13313549
Modeling of intra-die process variations for accurate analysis and optimization of nano-scale circuits
This paper proposes the use of Karhunen-Loeve expansion (KLE) for accurate and efficient modeling of intra-die correlations in the semiconductor manufacturing process. We demonstrate that the KLE provides a significantly more accurate representation, of the underlying stochastic process compared to the traditional approach of dividing the layout into grids and applying principal component analysis (PCA). By comparing the results of leakage analysis using both KLE and the existing approaches, we show that using KLE can provide up to 4-5times reduction in the variability space (number of random variables) while maintaining the same accuracy. We also propose an efficient leakage minimization algorithm that maximizes the leakage yield while satisfying probabilistic constraints on the delay
8145594
Effects of global interconnect optimizations on performance estimation of deep submicron design
In this paper, we quantify the impact of global interconnect optimization techniques that address such design objectives as delay, peak noise, delay uncertainty due to noise, power, and cost. In doing so, we develop a new system-performance simulation model as a set of studies within the MARCO GSRC Technology Extrapolation (GTX) system. We model a typical point-to-point global interconnect and focus on accurate assessment of both circuit and design technology with respect to such issues as inductance, signal line shielding, dynamic delay, buffer placement uncertainty and repeater staggering. We demonstrate, for example, that optimal wire sizing models need to consider inductive effects-and that use of more accurate (-1,3) worst-case capacitive coupling noise switch factors substantially increases peak noise estimates compared to traditional (0,2) bounds. We also find that optimal repeater sizes are significantly smaller than conventional models would suggest, especially when considering energy-delay issues.