33372839
3-D Facial Expression Recognition-Synthesis on PDA Incorporating Emotional Timing
This paper describes a pipeline by which facial expression of the face is recognized and then 3-D facial animation is synthesized in the remote place based upon timing information of the facial. The system first detects a facial area within the given image and then classifies its facial expression into 7 emotional weightings. Such weighting information, transmitted to the PDA via a mobile network, is used for non-photorealistic facial expression animation. A cartoon-like shading is used to render a 3-D avatar that conveys a familiar and yet unique facial character, even without employing extensive polygons. It turns out that facial expression animation using emotional curves is more effective in expressing the timing of an expression comparing to the linear interpolation method. The emotional avatar embedded on a mobile platform has some potential in conveying emotion between peoples in Internet.
37111410
Performance Comparison Between Backpropagation, Neuro-Fuzzy Network, and SVM
In this study, we compare the performance of well-known neural networks, namely, back-propagation (BP) algorithm, Neuro-Fuzzy network and Support Vector Machine (SVM) using the standard three database sets: Wisconsin breast cancer, Iris and wine data. Since such database have been useful for evaluating performance of a group of machine learning algorithms, a series of experiments have been carried out for three algorithms using the cross validation method. Results suggest that SVM outperforms the others and the Neuro-Fuzzy network is better than the BP algorithm for this data set.
33400437
Facial Expression Recognition Using Active Appearance Model
This paper describes a facial expression recognition system based upon Active Appearance Model (AAM), which has been typically used for the face recognition task. Given that AAM has been also used in tracking the moving object, we thought it could be effective in recognizing the facial expressions of humans. Our results show that the performance of the facial expression recognition using AAM is reliably high when it combined with an enhanced Fisher classification model.
6477815
An Affective User Interface Based on Facial Expression Recognition and Eye-Gaze Tracking
This paper describes a pipeline by which facial expression and eye-gaze of the user are tracked, and then 3D facial animation is synthesized in the remote place based upon timing information of the facial and eye movement information. The system first detects a facial area within the given image and then classifies its facial expression into 7 emotional weightings. Such weighting information, transmitted to the PDA via a mobile network, is used for non-photorealistic facial expression animation. It turns out that facial expression animation using emotional curves is more effective in expressing the timing of an expression comparing to the linear interpolation method. The emotional avatar embedded on a mobile platform has some potential in conveying emotion between peoples via Internet.
44579377
Head Detection and Tracking for the Car Occupant's Pose Recognition
This paper describes a Vision-based Occupant Pose Recognition (VOPR) system, which can ensure a safe airbag deployment. Head detection and its tracking are necessary for occupant’s pose recognition in the car, since the position of occupant’s head provides valuable information, such as his pose, size, position, and so on. We use the stereo cameras to extract a disparity map. Against variable lighting conditions including the night drive, we adopt infrared illumination as well as normal one. Results suggest that VOPR system is reliable and performs reasonably well.
14130132
Signal space detection for recording channels with jitter noise
A delay-constrained sequence detector is considered for recording channels whose major impediments include intersymbol interference (ISI) and magnetic transition jitter noise. The jitter noise is data-dependent, and a given noise sample is correlated with neighboring noise samples. A sequence detector with a finite decision delay can be formulated in a finite dimensional vector space. For a correlated noise channel, the decision boundary is generally quadratic. We present a technique for obtaining a minimal set of hyperplanes approximating a quadratic decision boundary with a negligible performance loss. In this process, a distance measure, which is consistent with the notion of the effective SNR, is defined and used as a design parameter to trade the complexity and performance. As an achievable performance bound, we derive the effective SNR for the maximum-likelihood sequence detector (MLSD) for these channels. The performance of the partial response maximum likelihood (PRML) detector commonly adopted for current data storage channels as well as the Viterbi algorithm (VA) based on the traditional Euclidean metric, which serves as the MLSD for additive white Gaussian noise, are also analyzed and compared with that of the proposed signal space detector.
199790
Secure group communication using robust contributory key agreement
Contributory group key agreement protocols generate group keys based on contributions of all group members. Particularly appropriate for relatively small collaborative peer groups, these protocols are resilient to many types of attacks. Unlike most group key distribution protocols, contributory group key agreement protocols offer strong security properties such as key independence and perfect forward secrecy. We present the first robust contributory key agreement protocol resilient to any sequence of group changes. The protocol, based on the Group Diffie-Hellman contributory key agreement, uses the services of a group communication system supporting virtual synchrony semantics. We prove that it provides both virtual synchrony and the security properties of Group Diffie-Hellman, in the presence of any sequence of (potentially cascading) node failures, recoveries, network partitions, and heals. We implemented a secure group communication service, Secure Spread, based on our robust key agreement protocol and Spread group communication system. To illustrate its practicality, we compare the costs of establishing a secure group with the proposed protocol and a protocol based on centralized group key management, adapted to offer equivalent security properties.
11689182
Decentralized Authentication Mechanisms for Object-based Storage Devices
Network-attached object-based storage separates data-path from control-path and enables direct interaction between clients and the storage devices. Clients interact with the file manager only to acquire the meta-data information and some cryptographic primitives, for example, access keys. Most of the current schemes rely on a centralized file manager to support these activities. This paper presents security mechanisms for decentralized authentication for object-based storage. The schemes are novel in several ways. First of all, they reduce the load on the file manager and free the system from central point of failure and denial of service attacks. We exploit Role-based Access Control (RBAC) to provide scalability and design authentication schemes that efficiently utilize RBAC. In most of the cases, the client needs to acquire only one access key from the file manager, which can be used by the client to further derive role-keys for the roles that he/she is permitted to play within an organization. Further, the number of cryptographic keys required for the purpose of authentication in these schemes is less as compared to the existing schemes. Finally, we also present two simple schemes that enable the clients to access objects stored on any device on the network using a single identity key.
30845722
Accurate exploration of timing and area trade-offs in arithmetic optimization using carry-save-adders
Timing and area of circuits are two of the most important design criteria to be optimized in data path synthesis. In addition, carry-save-adder (CSA) has been proven to be one of the most efficient implementation units in optimizing timing and/or area of arithmetic circuits. However, the existing approaches are restricted in using CSAs, i.e., optimizing operation trees separately without any interaction between them, resulting in a locally optimized CSA circuit. To overcome this limitation, we propose a practically efficient solution to the problem of an accurate exploration of timing and area trade-offs in optimizing arithmetic circuits in the presence of multiple operation trees using CSAs. The application of our approach is able to find a best CSA implementation of circuit in terms of timing and area.
18562018
2-Way Text Classification for Harmful Web Documents
The openness of the Web allows any user to access almost any type of information. However, some information, such as adult content, is not appropriate for all users, notably children. Additionally for adults, some contents included in abnormal porn sites can do ordinary people's mental health harm. In this paper, we propose an efficient 2-way text filter for blocking harmful web documents and also present a new criterion for clear classification. It filters off 0-grade web texts containing no harmful words using pattern matching with harmful words dictionaries, and classifies 1-grade,2-grade and 3-grade web texts using a machine learning algorithm.