12971605
AAM derived face representations for robust facial action recognition
In this paper, we present results on experiments employing active appearance model (AAM) derived facial representations, for the task of facial action recognition. Experimental results demonstrate the benefit of AAM-derived representations on a spontaneous AU database containing "real-world" variation. Additionally, we explore a number of normalization methods for these representations which increase facial action recognition performance
8192681
Image Retrieval Using Schwarz Representation of One-Dimensional Feature
Retrieval efficiency and accuracy are two important issues in designing a content based database retrieval system. In order to retrieve efficiently, we must extract feature to build index. Recently intensive research focused on how to extract one-dimensional features and calculate the distance between them, such as color histogram, Fourier descriptor, image shape spectrum (ISS). We develop a new method to match one-dimensional feature function in multiscale space using Schwarz representation. It can obtain closed form match function and similarity measure instead of traditional optimization. Thus we can calculate the global distance when the local information of feature function is matched. In this paper, we use the center distance function of shape as the feature functions. We calculate their Schwarz representation as indices, and calculate the optimal distance as similarity measure to sort the images. Experimental results show its efficiency and accuracy.
13451430
Non-negative matrix factorization framework for face recognition
Non-negative Matrix Factorization (NMF) is a part-based image representation method which adds a non-negativity constraint to matrix factorization. NMF is compatible with the intuitive notion of combining parts to form a whole face. In this paper, we propose a framework of face recognition by adding NMF constraint and classifier constraints to matrix factorization to get both intuitive features and good recognition results. Based on the framework, we present two novel subspace methods: Fisher Non-negative Matrix Factorization (FNMF) and PCA Non-negative Matrix Factorization (PNMF). FNMF adds both the non-negative constraint and the Fisher constraint to matrix factorization. The Fisher constraint maximizes the between-class scatter and minimizes the within-class scatter of face samples. Subsequently, FNMF improves the capability of face recognition. PNMF adds the non-negative constraint and characteristics of PCA, such as maximizing the variance of output coordinates, orthogonal bases, etc. to matrix factorization. Therefore, we can get intuitive features and desirable PCA characteristics. Our experiments show that FNMF and PNMF achieve better face recognition performance than NMF and Local NMF.
1952111
Manifold Based Analysis of Facial Expression
We propose a novel approach for modeling, tracking and recognizing facial expressions. Our method works on a low dimensional expression manifold, which is obtained by Isomap embedding. In this space, facial contour features are first clustered, using a mixture model. Then, expression dynamics are learned for tracking and classification. We use ICondensation to track facial features in the embedded space, while recognizing facial expressions in a cooperative manner, within a common probabilistic framework. The image observation likelihood is derived from a variation of the Active Shape Model (ASM) algorithm. For each cluster in the low-dimensional space, a specific ASM model is learned, thus avoiding incorrect matching due to non-linear image variations. Preliminary experimental results show that our probabilistic facial expression model on manifold significantly improves facial deformation tracking and expression recognition.
16132997
Manifold of facial expression
We propose the concept of manifold of facial expression based on the observation that images of a subject's facial expressions define a smooth manifold in the high dimensional image space. Such a manifold representation can provide a unified framework for facial expression analysis. We first apply active wavelet networks (AWN) on the image sequences for facial feature localization. To learn the structure of the manifold in the feature space derived by AWN, we investigated two types of embeddings from a high dimensional space to a low dimensional space: locally linear embedding (LLE) and Lipschitz embedding. Our experiments show that LLE is suitable for visualizing expression manifolds. After applying Lipschitz embedding, the expression manifold can be approximately considered as a super-spherical surface in the embedding space. For manifolds derived from different subjects, we propose a nonlinear alignment algorithm that keeps the semantic similarity of facial expression from different subjects on one generalized manifold. We also show that nonlinear alignment outperforms linear alignment in expression classification.
5138654
LISP: a link-indexed statistical traffic prediction approach to improving IEEE 802.11 PSM
We present a novel and complementary mechanism, called link-indexed statistical traffic predictor (LISP) to improve IEEE 802.11 power saving mechanism (PSM). LISP employs a simple, light-weight traffic prediction mechanism and enables each node to seek the inherent correlation between ATIM.ACKs and incoming traffic. Thereby nodes en route can stay awake in the BI in which a packet is anticipated to arrive, thus bridging a "freeway" for the packet to rapidly traverse the route. Meanwhile, the number of duty cycles is minimized and more energy is conserved. We conduct analytical and simulation studies and demonstrate the effectiveness of LISP.
14850039
Provisioning Quality Controlled Medium Access in UltraWideBand-Operated WPANs
Quality of service (QoS) provisioning is one of the most important criteria in newly emerging UWB-operated WPANs, as they are expected to support a wide variety of applica- tions from time-constrained, multimedia streaming to throughput- hungry, content transfer applications. As such, the Enhanced Distributed Coordinated Access (EDCA) mechanism has been adopted by MultiBand OFDM Alliance in its UWB MAC proposal. In this paper, we conduct a rigorous, comprehensive, theoretical analysis and show that with the currently recommended parame- ter setting, EDCA cannot provide adequate QoS. In particular, without responding to the system dynamics (e.g., taking into account of the number of active class-i stations), EDCA cannot allocate bandwidth in a deterministic proportional manner and the system bandwidth is under-utilized. After identifying the deficiency of EDCA, we propose, in compliance with the EDCA-incorporated UWB MAC protocol proposed in (15) (20), a framework, along with a set of theoretically grounded methods for controlling medium access with determin- istic QoS for UWB networks. We show that in this framework, 1) real-time traffic is guaranteed of deterministic bandwidth via a contention-based reservation access method; 2) best-effort traffic is provided with deterministic proportional QoS; and moreover, 3) the bandwidth utilization is maximized. We have also validated and evaluated the QoS provisioning capability and practicality of the proposed MAC framework both via simulation and empirically by leveraging the MADWifi (Multiband Atheros Driver for WiFi) Linux driver for Wireless LAN devices with the Atheros chipset.
9059175
On thermal effects in deep sub-micron VLSI interconnects
This paper presents a comprehensive analysis of the thermal effects in advanced high performance interconnect systems arising due to self-heating under various circuit conditions, including electrostatic discharge. Technology (Cu, low-k etc.) and scaling effects on the thermal characteristics of the interconnects, and on their electromigration reliability has been analyzed simultaneously, which will have important implications for providing robust and aggressive deep sub-micron interconnect design guidelines. Furthermore, the impact of these thermal effects on the design (driver sizing) and optimization of the interconnect length between repeaters at the upper-level signal lines are investigated.
14245590
RED with optimized dynamic threshold deployment on shared buffer
Prior survey of RED algorithm deployment on multiqueue system with shared buffer was unfair and sensitive to congestion level by statically setting the parameters. In this paper, our goal is to deploy the Random Early Detection (RED) algorithm in routers on shared buffer and solve these problems. A novel buffer management scheme that dynamically adjusts the parameters of RED named RED-ODT is proposed. Simulations under uniform traffic load and nonuniform traffic load are given, the results of which ascertain and demonstrate the superiority of the proposed scheme in terms of low packet drop ratio, satisfying buffer utilization and fairness. Simulation also shows that RED-ODT is insensitive to congestion level.
206993144
Charge-based core and the model architecture of BSIM5
The paper outlines the charge-based core and the architecture of the BSIM5 MOSFET model for sub-100 nm CMOS circuit simulation. The BSIM5 model is a continuous, completely symmetric and accurate non charge-sheet based MOS transistor model derived from the basic device physics, including various physics effects. Comparison of the inversion charge between the BSIM5 prediction and self-consistent numerical solution shows good agreement. The demonstration of fully symmetric characteristics of BSIM5, such as channel current and its high-order derivative in the Gummel symmetry test, and charge and trans-capacitances in a SPICE simulation, also implies BSIM5 is the physically symmetric MOSFET model valid for RF-analog circuit simulations.