39178482
Illumination invariant face recognition
The appearance of a face will vary drastically when the illumination changes. Variations in lighting conditions make face recognition an even more challenging and difficult task. In this paper, we propose a novel approach to handle the illumination problem. Our method can restore a face image captured under arbitrary lighting conditions to one with frontal illumination by using a ratio-image between the face image and a reference face image, both of which are blurred by a Gaussian filter. An iterative algorithm is then used to update the reference image, which is reconstructed from the restored image by means of principal component analysis (PCA), in order to obtain a visually better restored image. Image processing techniques are also used to improve the quality of the restored image. To evaluate the performance of our algorithm, restored images with frontal illumination are used for face recognition by means of PCA. Experimental results demonstrate that face recognition using our method can achieve a higher recognition rate based on the Yale B database and the Yale database. Our algorithm has several advantages over other previous algorithms: (1) it does not need to estimate the face surface normals and the light source directions, (2) it does not need many images captured under different lighting conditions for each person, nor a set of bootstrap images that includes many images with different illuminations, and (3) it does not need to detect accurate positions of some facial feature points or to warp the image for alignment, etc.
31880885
Channel-adaptive error protection for streaming stored MPEG-4 FGS over error-prone environments
In this paper, we investigate an adaptive channel error-protection scheme for streaming stored MPEG-4 fine granular scalability (FGS) bitstreams over error-prone environments. The human eye is sensitive to the variations in reconstructed image quality. Therefore, instead of using only the minimal average frame distortion as the optimization criterion, we propose a rate-distortion (R-D)-based bit-allocation method to determine the source coding rate and the channel coding rate under a given channel condition so as to minimize both the average image distortion and quality variation. Based on our proposed piecewise model of the MPEG-4 FGS enhancement layer, a balance between the average frame quality and quality variation will be obtained. Experimental results show that, compared with other existing methods, our proposed method can achieve less quality variation and comparable average frame distortion under various channel conditions.
28287084
Human face recognition based on spatially weighted Hausdorff distance
The edge map of a facial image contains abundant information about its shape and structure, which is useful for face recognition. To compare edge images, Hausdorff distance is an efficient measure that can determine the degree of their resemblance, and does not require a knowledge of correspondence among those points in the two edge maps. In this paper, a new modified Hansdorff distance measure is proposed, which has a better discriminant power. As different facial regions have different degrees of significance for face recognition, a new modified Hausdorff distance is proposed which is weighted according to a weighted function derived from the spatial information of the human face; hence crucial regions are emphasized for face identification. Experimental results show that the distance measure can achieve recognition rates of 80%, 87%, and 91% for the first, the first five, and the first seven likely matched faces, respectively.
14714935
An efficient low bit-rate video-coding algorithm focusing on moving regions
Block-based motion estimation and compensation are the most popular techniques for video coding. However, as the shape and the structure of an object in a picture are arbitrary, the performance of such conventional block-based methods may not be satisfactory. In this paper, a very low bit-rate video coding algorithm that focuses on moving regions is proposed. The aim is to improve the coding performance, which gives better subjective and objective quality than that of the conventional coding methods at the same bit rate. Eight patterns are pre-defined to approximate the moving regions in a macroblock. The patterns are then used for motion estimation and compensation to reduce the prediction errors. Furthermore, in order to increase the compression performance, the residual errors of a macroblock are rearranged into a block with no significant increase of high-order DCT coefficients. As a result, both the prediction efficiency and the compression efficiency are improved.
26133489
Robust Hausdorff distance for shape matching
The Hausdorff distance can be used to measure the similarity of two point sets. In matching the two point sets, one of them is translated, rotated and scaled in order to obtain an optimal matching, which is a computationally intensive process. In this paper, a robust line-feature-based approach for model-based recognition is presented, which can achieve good matching, even in a noisy environment or with the existence of occlusion. We propose three different ways for forming the line segments for a point set. Two of the methods are based on a fixed reference point, which are the centroid and the center of the minimal disk of the point set. The third method is based on the longest possible line segments formed within the point set. The line features extracted based on the respective line segments are insensitive to noise and can be used to determine the rotation and scale of the image point set accurately and reliably, and more importantly, 2D-2D matching algorithm can be adopted. The first 2D-matching is to compute the relative scale and orientation between the two point sets. Having rotated and scaled the image point set, the M-Estimation Hausdorff distance is applied for the second 2D-matching to measure the relative translation between the query point set and the model point set. This 2D-2D matching can greatly reduce the required memory and computation when compared to a 4D-matching. Both the performance and the sensitivity to noise of our algorithms are evaluated using simulated data. Experiments show that our 2D-2D algorithms can yield a high level of performance when determining the scale, the orientation and the similarity of two point sets.
721061
A fast fractal image coding based on kick-out and zero contrast conditions
A fast algorithm for fractal image coding based on a single kick-out condition and the zero contrast prediction is proposed in this paper. The single kick-out condition can avoid a large number of range-domain block matches when finding the best matched domain block. An efficient method for zero contrast prediction is also proposed, which can determine whether the contrast factor for a domain block is zero or not, and compute the corresponding difference between the range block and the transformed domain block efficiently and exactly. The proposed algorithm can achieve the same reconstructed image quality as the exhaustive search, and can greatly reduce the required computation or runtime. In addition, this algorithm does not need any pre-processing step or additional memory for its implementation, and can combine with other fast fractal algorithms to further improve the speed. Experimental results show that the runtime is reduced by about 50% of that of the exhaustive search method. When combined with the DCT Inner Product algorithm, the required runtime for the algorithm can be further reduced by about 50%. The proposed algorithm was also compared to two other fast fractal algorithms. Experimental results also show that our algorithm achieves a better efficiency and requires a much smaller amount of memory for implementation.
14189953
Adaptive record clustering
An algorithm for record clustering is presented. It is capable of detecting sudden changes in users' access patterns and then suggesting an appropriate assignment of records to blocks. It is conceptually simple, highly intuitive, does not need to classify queries into types, and avoids collecting individual query statistics. Experimental results indicate that it converges rapidly; its performance is about 50 percent better than that of the total sort method, and about 100 percent better than that of randomly assigning records to blocks.
16770370
Impact of priority assignment on optimistic concurrency control in distributed real-time databases
In the studies of real-time concurrency control protocols (RT-CCPs), it is always assumed that earliest deadline first (EDF) is employed as the CPU scheduling algorithm. However, using purely (ultimate) deadline for priority assignment may not be suitable for distributed real-time database systems (DRTDBS) in which there exist different kinds of transactions, such as global and local transactions. In order to improve the performance, different priority assignment heuristics have to be used. In this paper, we have investigated the performance of different priority assignment heuristics for sub-transactions in DRTDBS with optimistic concurrency control (OCC) protocol. If is found that the heuristics, which are suitable for distributed real-time systems, are not suitable for DRTDBS. We find that our proposed heuristic, which considers both deadline constraint and data contention, can give the best performance.
42222241
Efficient technique for performance analysis of locking protocols
The validity of many analytic studies of the performance of database systems are often hampered by the many approximations made. This is especially true of the way the block queue delays and deadlocks have been handled. An efficient approach to the derivation of the blocking delays of transactions under the static and dynamic two phase locking protocols is given. The problem of deadlocks which has either been neglected or assumed to be of cycle-length two (involving two transactions only) has also been tackled with some degree of success. The analysis is based on simple combinatorial arguments and probability theory. MVA techniques are then applied to the two models. Several conclusions can be drawn regarding the behaviour of the database systems. The analytic results show remarkable good agreement with simulation results.<<ETX>>
7762454
Cache invalidation scheme for mobile computing systems with real-time data
In this paper, we propose a cache invalidation scheme called Invalidation by Absolute Validity Interval (IAVI) for mobile computing systems. In IAVI, we define an absolute validity interval (AVI), for each data item based on its dynamic property such as the update interval. A mobile client can verify the validity of a cached item by comparing the last update time and its AVI. A cached item is invalidated if the current time is greater than the last update time plus its AVI. With this self-invalidation mechanism, the IAVI scheme uses the invalidation report to inform the mobile clients about changes in AVIs rather than the update event of the data items. As a result, the size of the invalidation report can be reduced significantly. Through extensive simulation experiments, we have found that the performance of the IVAI scheme is significantly better than other methods such as bit sequence and timestamp.
15094992
Evaluation of concurrency control strategies for mixed soft real-time database systems
Previous research in real-time concurrency control mainly focuses on the schedulability guarantee of hard real-time transactions and the reduction of the miss rate of soft real-time transactions. Although many new database applications have significant response time requirements, not much work has been done in the joint scheduling of traditional nonreal-time transactions and soft real-time transactions. In this paper, we study the concurrency control problems in mixed soft real-time database systems, in which both non-real-time and soft real-time transactions exist simultaneously. The objectives are to identify the cost and the performance tradeoff in the design of cost-effective and practical real-time concurrency control protocols, and to evaluate their performance under different real-time and non-real-time supports. In particular, we are interested in studying the impacts of different scheduling approaches for soft real-time transactions on the performance of non-real-time transactions. Instead of proposing yet another completely new real-time concurrency control protocol, our objective is to design an efficient integrated concurrency control method based on existing techniques. We propose several methods to integrate the well-known two phase locking and optimistic concurrency control with the aims to meet the deadline requirements of soft real-time transactions and, at the same time, to minimize the impact on the performance of non-real-time transactions. We have conducted a series of experiments based on a sanitized version of stock trading systems to evaluate the performance of both soft real-time and non-real-time transactions under different real-time supports in the system.