14661776
Pose Estimation Based on Gaussian Error Models
In this paper, a new method is presented to estimate the 3D pose of facial image based on statistical Gaussian error models. The basic idea is that the pose angle can be computed by the orthogonal projection computation if the specific 3D shape vector of the given person is known. In our algorithm, Gaussian probability density function is used to model the distributions of the 3D shape vector as well as the errors between the orthogonal projection computation and the weak perspective projection. By using the prior knowledge of the errors distribution, the most likely 3D shape vector can be referred by the labeled 2D landmarks in the given facial image according to the maximum posterior probability theory. Refining the error term, thus the pose parameters can be estimated by the transformed orthogonal projection formula. Experimental results on real images are presented to give the objective evaluation.
426930
An admission control scheme for end-to-end statistical QoS provision in IP networks
This paper presents a distributed and scalable admission control scheme to provide end-to-end statistical QoS guarantees in IP network. The basic idea of the scheme is that the ingress routers make admission control decisions according to the network status information obtained by sending probing packets along the selected routing path. Each router passively monitors the arriving traffic and marks the probing packets with its network status. The performance of the presented scheme is evaluated with a variety of traffic models, QoS metrics and network topologies. The simulation results show that the proposed scheme can accurately control the admissible region and effectively improve the utilization of network resource.
7272862
Linear transform based motion compensated prediction for luminance intensity changes
A linear transform based motion compensated prediction (LT-MCP) scheme is proposed in this paper to improve the efficiency of inter-frame prediction when the intensity of luminance changes abruptly across frames. Either uniform or non-uniform intensity changes can be well processed as the proposed scheme is applied at macroblock (MB) level. LT-MCP is implemented based on the H.264 reference software to evaluate its performance. For those sequences with significant luminance changes across frames, such as Crew, we can achieve about 1.5dB improvement over the conventional MCP with intra prediction disabled and about 0.8dB gain with intra prediction enabled. For those sequences without obvious luminance changes, the proposed scheme also works better.
11924885
Distributed video coding using wavelet
This paper proposes a distributed video coding scheme based on the zero tree entropy (ZTE) coding. Wyner-Ziv theory on source coding with side information is taken as the basic coding principle, which makes independent encoding and joint decoding possible. In this scheme, wavelet transform is used to exploit the spatial correlation of a Wyner-Ziv frame. The quantized wavelet coefficients are reorganized in terms of the zero tree structure so as to identify the significant and insignificant coefficients. The significance map is intra-codec and transmitted. In particular, the significant coefficients are independently encoded with turbo coder, and only the parity bits are transmitted. At the decoder, a predictive frame generated through motion-compensated prediction is used as the side information, with which the Wyner-Ziv frame can be conditionally decoded. Experimental results show that, compared to the traditional intra-frame coding and pixel-domain Wnyer-Ziv video coding, the proposed scheme can achieve a better coding performance, especially at low bit rates
58983783
Review the strength of Gabor features for face recognition from the angle of its robustness to mis-alignment
Gabor feature has been widely recognized as better representation for face recognition in terms of rank-1 recognition rate. In this paper, we review the strength of Gabor feature for face recognition from the new angle of its robustness to mis-alignment using a novel quantificational evaluation method combining both the alignment precision and the recognition accuracy. Our experiments show that, compared with the gray-level intensity, Gabor feature is much more robust to image variation caused by the imprecision of facial feature localization, which further support the feasibility of Gabor representation.
41595049
Robust speech recognition method based on discriminative environment feature extraction
It is an effective approach to learn the influence of environmental parameters, such as additive noise and channel distortions, from training data for robust speech recognition. Most of the previous methods are based on maximum likelihood estimation criterion. However, these methods do not lead to a minimum error rate result. In this paper, a novel discriminative learning method of environmental parameters, which is based on Minimum Classification Error (MCE) criterion, is proposed. In the method, a simple classifier and the Generalized Probabilistic Descent (GPD) algorithm are adopted to iteratively learn the envirnnmental parameters. Consequently, the clean speech features are estimated from the noisy speech features with the estimated environmental parameters, and then the estimations of clean speech features are utilized in the back-end HMM classifier. Experiments show that the best error rate reduction of 32.1% is obtained, tested on a task of 18 isolated confusion Korean words, relative to aconventional HMM system.
39810254
NCPN: A Simulation Tool for Coloured Petri Nets
36162111
Reconstruction problems in 3D for viral cryo electron microscopy
Cryo electron microscopy of viruses provides 2D projections of the scattering intensity of the viral particle but the orientation of the projections is not known. We describe an approach to reconstructing the 3D scattering intensity in spite of the unknown projection orientations using nonlinear least squares ideas where the reconstruction is guaranteed to have the icosahedral symmetry known to be present in the viral particle.
6724826
Spectrum Sensing Using Cyclostationary Properties and Application to IEEE 802.22 WRAN
Spectrum sensing in a very low SNR environment (less than -20 dB) is considered in this paper. We make use of the noise rejection property of the cyclostationary spectrum. The sensing algorithms are based on measurement of the cyclic spectrum of the received signals. The statistics of the cyclic spectrum of the stationary white Gaussian process are fully analyzed for three measurement methods of the cyclic spectrum. The application to IEEE 802.22 WRAN is presented and the probability of false alarm is analytically derived. The operating characteristic curves for the sensing algorithms are determined from computer simulations using ATSC A/74 DTV signal captures as a test database.
46501259
A proactive fault-detection mechanism in large-scale cluster systems
7918052
Fast Identification of Error-Prone Patterns for LDPC Codes under Message Passing Decoding
Although density evolution accurately predicts the asymptotic performance of LDPC codes, it provides limited information for codes of short or moderate block length. For this reason, combinatorial methods have been employed to analyze the performance of finite-length LDPC codes under message passing decoding. The error floor phenomenon is a key issue of finite-length effects, which is caused largely by poorly connected subgraphs residing in the LPDC codes structure. Because of the unequal noise immunity of different bit levels, error floors become more pronounced for LDPC-coded high-order modulation. Nevertheless, the enumeration of error-prone patterns that lead to error floors has been proven to be NP-hard, which motivates us to find substitute metrics with manageable complexity. Considering trapping sets always comprise loops of low extrinsic message degree (EMD) and the connectivity of a loop with the residual graph can be characterized by its approximate EMD (ACE), in this paper we propose a fast method to identify loops with low ACE for a given code. In light of this, the vulnerable variable nodes residing on low-ACE loops are judiciously mapped to bit levels benefitting from stronger error protection. As a result, the error floor can be significantly improved at the cost of a minor increase of hardware complexity.