S. Vasuhi

Identification of Human Faces Using Orthogonal Locality Preserving Projections

This paper presents a technique for identification of human faces using an algorithm based on Orthogonal Locality Preserving Projections (OLPP). It differs from Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), which preserves the Euclidean structure of face space. Locality Preserving Projections (LPP) finds an embedding that preserves local information, and obtains a face subspace that best detects the essential manifold structure. Locality Preserving Projections (LPP) is non-orthogonal, and this makes it difficult to reconstruct the data. This problem is overcome by using Orthogonal Locality Preserving Projection method which produces orthogonal basis functions and can have more locality preserving power than LPP. Since the locality preserving power is potentially related to the discriminating power, the OLPP is expected to have more discriminating power than LPP. This approach, builds an adjacency graph which best reflects the geometry of the face manifold and the class relationship between various points. The projection is then obtained by preserving such graph structure which forms the Orthogonal Laplacianface. In this way, the unwanted variations resulting from changes in lighting, facial expression and poses are reduced.

Multiple Maneuvering Target Tracking Using MHT and Nonlinear Non-Gaussian Kalman Filter

In this paper, an algorithm for tracking multiple maneuvering targets by Multiple Hypothesis Tracking (MHT) with nonlinear non-Gaussian Kalman filter is investigated. The main challenges in multiple maneuvering targets tracking are the nonlinearity and non -Gaussianity problems. The Multiple Hypothesis Tracking (MHT) is used to detect the multiple targets in maneuverable and non-maneuverable modes. The computational requirements increase exponentially with number of tracks, the backscan depth and this can be reduced by careful design and tuning of MHT. The 1-backscan MHT algorithm is a good compromise between the two conflicting requirements of good tracking performance and limitation of computation time. The nonlinear non-Gaussian Kalman filter is used to track the target with high maneuver rate. The nonlinear non-Gaussian Kalman filter is implemented in MHT to give less probability of missing the target. The 1-backscan MHT with nonlinear non-Gaussian Kalman filter is free from computational burden by using simple probability concepts. This method of tracking also shows the reduction in the overshoot of root mean square error (RMSE).

Decision Level Fusion Framework for Face Authentication System

In this paper, multiple algorithm and score-level fusion for enhancing the performance of the face based biometric person authentication system is proposed. Though many algorithms are conferred, several crucial issues are still involved in the face authentication. Most traditional algorithms are based on certain assumptions failing which the system will not give appropriate results. Due to the inherent variations in face with time and space, it is a big challenge to formulate a single algorithm based on the face biometric that works well under all variations. This paper addresses the problem of illumination and pose variations, by using three different algorithms for face recognition: Block Independent Component Analysis (B-ICA), Discrete Cosine Transform (DCT) and Kalman filter. The weighted average based score level fusion is performed to improve the results obtained by the system. An intensive analysis of the various algorithms has been performed and the results indicate an increase in accuracy of the proposed system.

Multiple Maneuvering Targets Tracking Using Kalman and Real-Time Particle Filter A Comparison

In this paper, a comparison between thetwo algorithms for tracking multiple maneuvering targets in heavy clutter is done. First one is by using Multiple Hypothesis Tracking (MHT) and nonlinear non-Gaussian Kalman filter and the second one is by combining MHT and Real-Time Particle Filter (RTPF). The main difficulty in multiple maneuvering targets tracking is the nonlinearity associated with target states. The multiple targets motion modes in highly non-linear states are detected by using Multiple Hypothesis Tracking (MHT). In MHT, hypothetical tracks are generated, so the computational burden increases exponentially with number of tracks. So the 1-backscan MHT algorithm is a good alternative because its having good tracking performance and limitation of computation time. The nonlinear non-Gaussian Kalman filter is used to track the target with high maneuver rate and also it gives less probability of missing the target. Tracking by Real-time particle filter (RTPF) uses all sensor information even when the filter update rate is below than that of sensors. In RTPF each posterior is represented as mixture of sample sets, where each mixture component integrates one observation arriving during a filter update. RTPF eliminate the problem of filter divergence due to an insufficient number of independent samples.

Multi Sensor Data Fusion Methods Using Sensor Data Compression and Estimated Weights

When data fusion is performed in a distributed environment, it improves accuracy but the constraints are limited communication bandwidth and limited processing capability at the fusion center. So, it is crucial to compress the data at the fusion center. This is accomplished by reducing the dimension of the data. Based on the Linear Estimation and weighted least square fusion results, a method is presented for compressing data at each local sensor to improve the accuracy of the fused estimates. Another method for multi sensor data fusion with estimated weights is also suggested in this paper which also improves the accuracy of the fused estimates.

Design of CDMA MAC for Microsatellite

Code division multiple access (CDMA) is a digital wireless transmission technology that allows for a large amount of users to share access to a single radio channel. This technology is being widely used in cellular communication and can be extended to store and forward (S&F) payload that provides message relay service for several users with ground terminals, simultaneously. In this paper, the three layered model for the store and forward payload using CDMA medium access control (MAC) is considered. Their design methodologies are discussed assuming static code assignment