Solving the small sample size problem in face recognition using generalized discriminant analysis

The goal of face recognition is to distinguish persons via their facial images. Each person's images form a cluster, and a new image is recognized by assigning it to the correct cluster. Since the images are very high-dimensional, it is necessary to reduce their dimension. Linear discriminant analysis (LDA) has been shown to be effective at dimension reduction while preserving the cluster structure of the data. It is classically defined as an optimization problem involving covariance matrices that represent the scatter within and between clusters. The requirement that one of these matrices be nonsingular restricts its application to datasets in which the dimension of the data does not exceed the sample size. For face recognition, however, the dimension typically exceeds the number of images in the database, resulting in what is referred to as the small sample size problem. Recently, the applicability of LDA has been extended by using the generalized singular value decomposition (GSVD) to circumvent the nonsingularity requirement, thus making LDA directly applicable to face recognition data. Our experiments confirm that LDA/GSVD solves the small sample size problem very effectively as compared with other current methods.     

A stochastic realization algorithm via block LQ decomposition in Hilbert space

A stochastic realization problem of a stationary stochastic process is re-visited, and a new stochastically balanced realization algorithm is derived in a Hilbert space generated by second-order stationary processes. The present algorithm computes a stochastically balanced realization by means of the singular value decomposition of a weighted block Hankel matrix derived by a “block LQ decomposition”. Extension to a stochastic subspace identification method explains how the proposed abstract algorithm is implemented in system identification.     

On properties of RDT communication-induced checkpointing protocols

Rollback-dependency trackability (RDT) is a property stating that all rollback dependencies between local checkpoints are online trackable by using a transitive dependency vector. The most crucial RDT characterizations introduced in the literature can be represented as certain types of RDT-PXCM-paths. Here, let the U-path and V-path be any two types of RDT-PXCM-paths. We investigate several properties of communication-induced checkpointing protocols that ensure the RDT property. First, we prove that if an online RDT protocol encounters a U-path at a point of a checkpoint and communication pattern associated with a distributed computation, it also encounters a V-path there. Moreover, if this encountered U-path is invisibly doubled, the corresponding encountered V-path is invisibly doubled as well. Therefore, we can conclude that breaking all invisibly doubled U-paths is equivalent to breaking all invisibly doubled V-paths for an online RDT protocol. Next, we continue to demonstrate that a visibly doubled U-path must contain a doubled U-cycle in the causal past. These results can further deduce that some different checkpointing protocols actually have the same behavior for all possible patterns. Finally, we present a commendatory systematic technique for comparing the performance of online RDT protocols.     

Effect of Thickness of the p-AlGaN Electron Blocking Layer on the Improvement of ESD Characteristics in GaN-Based LEDs

The following letter presents a study regarding GaN-based light-emitting diodes (LEDs) with p-type AlGaN electron blocking layers (EBLs) of different thicknesses. The study revealed that the LEDs could endure higher electrostatic discharge (ESD) levels as the thickness of the AlGaN EBL increased. The observed improvement in the ESD endurance ability could be attributed to the fact that the thickened p-AlGaN EBL may partly fill the dislocation-related pits that occur on the surface of the InGaN-GaN multiple-quantum well (MQW) and that are due to the strain and the low-temperature-growth process. If these dislocation-related pits are not partly suppressed, they will eventually result in numerous surface pits associated with threading dislocations that intersect the InGaN-GaN (MQW), thereby reducing the ESD endurance ability. The results of the experiment show that the ESD endurance voltages could increase from 1500 to 6000 V when the thickness of the p-AlGaN EBL in the GaN LEDs is increased from 32.5 to 130 nm, while the forward voltages and light output powers remained almost the same.     

Fundamental properties of reset control systems

Reset controllers are linear controllers that reset some of their states to zero when their input is zero. We are interested in their feedback connection with linear plants, and in this paper we establish fundamental closed-loop properties including stability and asymptotic tracking. This paper considers more general reset structures than previously considered, allowing for higher-order controllers and partial-state resetting. It gives a testable necessary and sufficient condition for quadratic stability and links it to both uniform bounded-input bounded-state stability and steady-state performance. Unlike previous related research, which includes the study of impulsive differential equations, our stability results require no assumptions on the evolution of reset times.     

Pedestrian detection and tracking at crossroads

This paper presents a system that can perform pedestrian detection and tracking using vision-based techniques. A very important issue in the field of intelligent transportation system is to prevent pedestrians from being hit by vehicles. Recently, a great number of vision-based techniques have been proposed for this purpose. In this paper, we propose a vision-based method, which combines the use of a pedestrian model as well as the walking rhythm of pedestrians to detect and track walking pedestrians. Through integrating some spatial and temporal information grabbed by a vision system, we are able to develop a reliable system that can be used to prevent traffic accidents happened at crossroads. In addition, the proposed system can deal with the occlusion problem. Experimental results obtained by executing some real world cases have demonstrated that the proposed system is indeed superb.     

An immune oriented multi-agent system for biological image processing

In this article, we present a parallel image processing system based on the concept of reactive agents. Our system lies in the oRis language, which allows to describe finely and simply the agents’ behaviors to detect image features. We also present a method of segmentation using a multi-agent system, and two biological applications made with oRis. The stopping of this multi-agent system is implemented through a technique issued from immunology: the apoptosis.