21848565
Discrete signal matching using coarse-to-fine wavelet basis functions
In this paper, we propose a matching algorithm to estimate accurate and dense displacements between two signals. The displacements are characterized by a coarse-to-fine wavelet representation, which is a linear combination of hierarchical basis functions developed by Cai and Wang (SIAM Numer. Anal. 33(3) (1996) 937). The coarser-scale basis function has larger support while the finer-scale basis function has smaller support. During the iterative minimization process, the basis functions are utilized as large-to-small windows in selecting global-to-local regions for signal matching. The estimated wavelet coefficients are then used to reconstruct the signal in a coarse-to-fine manner. Two sets of synthetic examples, one with small displacement and the other with large displacements, have been employed to illustrate the advantages of the wavelet-based method. This method has been applied to estimate the dense disparity between stereo images in several real examples and the results demonstrate its effectiveness.
10243856
A new LDA-based face recognition system which can solve the small sample size problem
A new LDA-based face recognition system is presented in this paper. Linear discriminant analysis (LDA) is one of the most popular linear projection techniques for feature extraction. The major drawback of applying LDA is that it may encounter the small sample size problem. In this paper, we propose a new LDA-based technique which can solve the small sample size problem. We also prove that the most expressive vectors derived in the null space of the within-class scatter matrix using principal component analysis (PCA) are equal to the optimal discriminant vectors derived in the original space using LDA. The experimental results show that the new LDA process improves the performance of a face recognition system signi"cantly. ( 2000 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
120801
Recognition of Motor Imagery Electroencephalography Using Independent Component Analysis and Machine Classifiers
Motor imagery electroencephalography (EEG), which embodies cortical potentials during mental simulation of left or right finger lifting tasks, can be used to provide neural input signals to activate a brain computer interface (BCI). The effectiveness of such an EEG-based BCI system relies on two indispensable components: distinguishable patterns of brain signals and accurate classifiers. This work aims to extract two reliable neural features, termed contralateral and ipsilateral rebound maps, by removing artifacts from motor imagery EEG based on independent component analysis (ICA), and to employ four classifiers to investigate the efficacy of rebound maps. Results demonstrate that, with the use of ICA, recognition rates for four classifiers (fisher linear discriminant (FLD), back-propagation neural network (BP-NN), radial-basis function neural network (RBF-NN), and support vector machine (SVM)) improved significantly, from 54%, 54%, 57% and 55% to 70.5%, 75.5%, 76.5% and 77.3%, respectively. In addition, the areas under the receiver operating characteristics (ROC) curve, which assess the quality of classification over a wide range of misclassification costs, also improved from .65, .60, .62, and .64 to .74, .76, .80 and .81, respectively.
9822806
Wavelet-based optical flow estimation
In this paper, a new algorithm for accurate optical flow estimation using discrete wavelet approximation is proposed. The proposed method takes advantages of the nature of wavelet theory, which can efficiently and accurately represent "things", to model optical flow vectors and image related functions. Each flow vector and image function are represented by linear combinations of wavelet basis functions. From such wavelet-based approximation, the leading coefficients of these basis functions carry the global information of the approximated "things". The proposed method can successfully convert the problem of minimizing a constraint function into that of solving a linear system of a quadratic and convex function of wavelet coefficients. Once all the corresponding coefficients are decided, the flow vectors can be determined accordingly. Experiments conducted on both synthetic and real image sequences show that our approach outperformed the existing methods in terms of accuracy.
17373350
VLSI architecture design of MPEG-4 shape coding
This paper presents an efficient VLSI architecture design of MPEG-4 shape coding, which is the key technology for supporting the content-based functionality of the MPEG-4 video standard. The real-time constraint of MPEG-4 shape coding leads to a heavy computational bottleneck on today's computer architectures. To overcome this problem, design analysis and optimization of MPEG-4 shape coding are addressed. By utilizing the RISC-based model, computational behaviors of the MPEG-4 shape coding tool are carefully examined and analyzed. The characteristic of a large amount of bit-level data processing and data transfer of MPEG-4 shape coding motivates the optimization of bit-level data operations. Applying data-flow optimization and data reuse techniques, bit-level computation-efficient architectures, such as data-dispatch-based binary-shaped motion estimation, the delay-line model, and configurable context-based arithmetic coding, are designed to accelerate bit-level processing. These hardware blocks are integrated and scheduled in a very efficient data flow to achieve real-time performance for MPEG-4 CPL2 (core profile level 2) specification at 23.5 MHz clock rate. The system architecture is implemented using Verilog HDL and synthesized with a 0.35 /spl mu/m four-layer CMOS standard library.
335267
VLSI implementation of shape-adaptive discrete wavelet transform
In this paper, several VLSI architectures and implementations of Shape-Adaptive Discrete Wavelet Transform (SA-DWT) with odd symmetric biorthogonal filters are presented. The hardware implementation issues of SA-DWT algorithm are first addressed, and one lifting scheme together with some appropriate shape information processing units is introduced for the 1-D SA-DWT architectures. These architectures can efficiently perform 1-D length-adaptive DWT on continuous line segments and solve the corresponding boundary extension and subsampling problems without any overhead. In addition to 1-D architectures, two 2-D SA-DWT architectures are also proposed. One is the direct method, which uses the 1-D SA-DWT architectures as basis to extend to 2-D SA-DWT by direct row-column approach. The other is the line-based method, which is an efficient and feasible architecture that uses internal line buffers rather than external frame memory. These two 2-D SA-DWT architectures are both VLSI implemented by using cell-based chip design flow. The Daubechies (9,7) filter is used for the implementation by direct method, and the Daubechies (9,3) filter is used for the line-based implementation. The proposed architectures can be applied both in arbitrarily shaped visual objects coding such as MPEG-4 still texture coding and rectangular region image coding such as JPEG2000 still image coding.
25000873
Design, analysis, and implementation of an agent driven pull-based distributed video-on-demand system
The problem of employing multiple servers to serve a pool of clients on a network based multimedia service is addressed. We have designed and practically implemented a prototype system employing multiple servers to render a long duration movie to the customers. We have employed a multiple server retrieval strategy proposed in the literature [39] to realize this system. In the system, server coordination, client behavior and service facilities are completely controlled by an Agent based approach in which we have used the recent Jini technology. Several issues, ranging from data retrieval from individual server, behavior of the underlying network infrastructure, to client management and resource (client buffers) management, are considered in this implementation. We describe in detail our experiences in this complete design process of every module in the software architecture, its purpose, and working style. Further, the system is shown to be robust amidst unpredictable failures, i.e., in the event of server crashes. The load balancing capability is built-in as a safe guard measure to assure a continuous presentation. We present a comprehensive discussion on the software architecture to realize this working system and present our experiences. A system comprising a series of Pentium III PCs on a fast Ethernet network is built as a test-bed. Through this prototype, a wider scope of research challenges ahead are highlighted as possible extensions.
206952974
High throughput CORDIC-based systolic array design for the discrete cosine transform
In this paper, we propose a modified Malvar algorithm that can transfer the Discrete Hartley Transform (DHT) results to the Discrete Cosine Transform (DCT) by using a one additional CORDIC computing stage. A fast CORDIC-based systolic array is designed with four attractive features the single/double data folding feature; the constructive feature; the co-computing feature; and redundant path computation. Due to the existence of the redundant path, the proposed design also has the capability of error detection.<<ETX>>
5417653
On the Web Data Extraction Model