45398591
A One Bit Facial Asymmetry Code (FAC) in Fourier Domain for Human Recognition
The present paper introduces a novel set of biometrics based on facial asymmetry measures in the frequency domain using a compact one-bit representation. A simplistic Hamming distance-type classifier is proposed as a means for matching bit patterns for identification purposes which is more efficient than PCA-based classifiers from storage and computation point of view, and produces equivalent results. A comparison with spatial intensity-based asymmetry measures suggests that our proposed measures are more robust to intra-personal distortions with a misclassification rate of only 4.24% on the standard facial expression database (Cohn-Kanade) consisting of 55 individuals. In addition, a rigorous statistical analysis of the matching algorithm is presented. The role of asymmetry of different face parts (e.g., eyes, mouth, nose) is investigated to determine which regions provide the maximum discrimination among individuals under different expressions.
8080205
Using Feature Combination and Statistical Resampling for Accurate Face Recognition Based on Frequency Domain Representation of Facial Asymmetry
This paper explores the efficiency of facial asymmetry in face identification tasks using a frequency domain representation. Satisfactory results are obtained for two different tasks, namely, human identification under extreme expression variations and expression classification, using a PCA-type classifier on a database with 55 individuals, which establishes the robustness of these measures to intra-personal distortions. Furthermore, we demonstrate that it is possible to improve upon these results significantly by simple means such as feature set combination and statistical resampling methods like bagging and random subspace method (RSM) using the same PCA-type base classifier. This even succeeds in attaining perfect classification results with 100% accuracy in some cases. Moreover, both these methods require few additional resources (computing time and power), hence they are useful for practical applications as well and help establish the effectiveness of frequency domain representation of facial asymmetry in automatic identification tasks
35096806
Human Face Identification from Video Based on Frequency Domain Asymmetry Representation Using Hidden Markov Models
In this paper we introduce a novel human face identification scheme from video data based on a frequency domain representation of facial asymmetry. A Hidden Markov Model (HMM) is used to learn the temporal dynamics of the training video sequences of each subject and classification of the test video sequences is performed using the likelihood scores obtained from the HMMs. We apply this method to a video database containing 55 subjects showing extreme expression variations and demonstrate that the HMM-based method performs much better than identification based on the still images using an Individual PCA (IPCA) classifier, achieving more than 30% improvement.
10906898
The Role of Statistical Models in Biometric Authentication
The current paper demonstrates the role of statistical models in authentication tasks – both in system development and in performance evaluation. We first introduce a model-based face authentication system based on the Fourier domain phase using Gaussian Mixture Models (GMM) which yields verification error rates as low as 0.3% on a face database of 65 individuals with extreme illumination variations. We then present a statistical framework for predicting authentication error rates for future populations in a rigorous way. This is in contrast to most evaluation protocols used today that are based on observational studies and valid only for the databases at hand. Applications establish that our model-based approach has better predictive performance than an existing state-of-the-art authentication technique.
15801848
A Design Diversity Metric and Analysis of Redundant Systems
Redundant systems are designed using multiple copies of the same resource (e.g., a logic network or a software module) in order to increase system dependability. Design diversity has long been used to protect redundant systems from common-mode failures. The conventional notion of diversity relies on "independent" generation of "different" implementations. This concept is qualitative and does not provide a basis for comparing the reliabilities of two diverse systems. In this paper, for the first time, we present a metric to quantify diversity among several designs and illustrate its effectiveness using several examples. Applications of this metric in analyzing reliability and availability of diverse redundant systems, and deriving simple relationships between diversity, system failure rate, and mission time are also demonstrated.
13125035
Automated Design of Misaligned-Carbon-Nanotube-Immune Circuits
Carbon nanotube field-effect transistors (CNFETs) are promising candidates as extensions to silicon CMOS due to excellent CV/I device performance. An ideal CNFET inverter fabricated using a perfect CNFET technology can have 5.1 times faster FO4 delay and 2.6 times lower energy per cycle compared to a 32 nm silicon CMOS inverter. Two fundamental challenges prevent us from creating CNFET-based logic designs with the advantages quoted above: 1. misaligned carbon nanotubes (CNTs), and 2. Metallic CNTs. Misaligned CNTs can result in incorrect logic function implementations. This paper presents a technique for designing CNFET-based arbitrary logic functions that are guaranteed to be correct even in the presence of a large number of misaligned CNTs.
2734062
A design diversity metric and reliability analysis for redundant systems
Design diversity has long been used to protect redundant systems against common-mode failures. The conventional notion of diversity relies on "independent" generation of "different" implementations. This concept is qualitative and does not provide a basis to compare the reliabilities of two diverse systems. In this paper, for the first time, we present a metric to quantify diversity among several designs. Based on this metric, we derive analytical reliability models that show a simple relationship between design diversity, system failure rate, and mission time. In addition, we present simulation results to demonstrate the effectiveness of design diversity in Duplex and Triple Modular Redundant (TMR) systems. For independent multiple-module failures, we show that, mere use of different implementations does not always guarantee higher reliability compared to redundant systems with identical implementations-it is important to analyze the reliability of redundant systems using our metric. For common-mode failures and design faults, there is a significant gain in using different implementations-however, as our analysis shows, the gain diminishes as the mission time increases. Our simulation results also demonstrate the usefulness of diversity for enhancing the self-testing properties of redundant systems.
15807495
Application-independent testing of FPGA interconnects
We present a new automatic test-configuration-generation technique for application-independent manufacturing testing of the interconnection network of static-random-access-memory-based field programmable gate arrays (FPGAs). This technique targets detection of open and bridging faults in the wiring channels and programmable switches in the interconnects. Experimental results on Xilinx Virtex FPGAs show that very few test configurations are required to cover stuck-open, stuck-closed, open, and bridging faults in the interconnects.
36794837
Dependable reconfigurable computing design diversity and self repair
Summary form only given, as follows. We demonstrate the power of reconfigurable computing in enabling cost-effective implementations of dependable systems. New concurrent error detection techniques based on practical implementations of design diversity are presented Field reconfigurability of reconfigurable hardware is utilized to design self-healing systems capable of autonomous recovery and repair from temporary errors and permanent faults. The applicability of these techniques are demonstrated through implementations on commercial reconfigurable hardware platforms. An error detection scheme based on diverse duplication compares the outputs of two "different" implementations of the same function and indicates error when a mismatch occurs. The idea of such a technique is derived from the general concept of design diversity. The conventional notion of design diversity is qualitative and relies on "independent" generation of "different" implementations. A metric to quantify design diversity is presented along with synthesis algorithms to efficiently design systems with error detection based on diverse duplication. In traditional dependable systems using hardware redundancy, fault tolerance is realized by detecting errors and locating the faulty chip or faulty board (Field Replaceable Unit or FRU) to be replaced by field service engineers. For systems designed using reconfigurable hardware, the FRU is very fined-grained such as a logic block or a routing resources (e.g., a pass-transistor based switch or a logic lookup table in Field Programmable Gate Arrays). Thus, in the case of a permanent fault, a cost-effective repair scheme is obtained using an alternative configuration in which the faulty parts are replaced with originally unused resources. A new self-repairing reconfigurable computing architecture based on dual FPGAs with embedded "soft" micro-controllers is presented This architecture allows the implemented system to recover from temporary errors and repair itself from permanent faults with minimum impact on system performance while ensuring very high data integrity and availability without external intervention. These capabilities make this architecture useful for a variety of dependable applications including unmanned remote applications such as deep space exploration.