2455352
Unified Principal Component Analysis with generalized Covariance Matrix for face recognition
Recently, 2DPCA and its variants have attracted much attention in face recognition area. In this paper, some efforts are made to discover the underlying fundaments of these methods, and a novel framework called unified principal component analysis (UPCA) is proposed. First, we introduce a novel concept, named generalized covariance matrix (GCM), which is naturally derived from the traditional covariance matrix (CM). Each element of GCM is a generalized covariance of two random vectors rather than two scalar variables in CM. Based on GCM, the UPCA framework is proposed, from which the traditional PCA and its 2D counterparts can be deduced as special cases. Furthermore, under the UPCA framework, we not only revisit the existing 2D PCA methods and their limitations, but also propose two new methods: the grid-sampling method (GridPCA) and the intra-group correlation reduction method. Extensive experimental results on the FERET face database support the theoretical analysis and validate the feasibility of the proposed methods.
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.
481878
Reducing Spatial Resolution for MPEG-2 to H.264/AVC Transcoding
Transcoding is an important technique for reducing the bit rate or spatial resolution to meet the constrained transmission bandwidths and terminal capabilities. In this paper, we propose a spatial downscaling transcoding method to convert an MPEG-2 bitstream into an H.264/AVC bitstream. A novel feature of the proposed method is to focus on the fast mode decision that fully exploits the advantages of variable block-size motion compensation feature in H.264/AVC. In the transcoder, types and motion vectors of pre-encoded macroblocks are considered together to decide the new encoding block type. While maintaining a reasonable image quality, the proposed method significantly reduces the computational complexity and facilitates the video servers to provide multimedia service in real time for heterogeneous clients. Experimental results show that our method is very effective.
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.
15693719
Context-based Arithmetic Coding Reexamined for DCT Video Compression
This paper presents a new context modeling technique for arithmetic coding of DCT coefficients in video compression. A key feature of the new technique is the inclusion of all previously coded coefficient magnitudes in a DCT block in context modeling. This enables adaptive arithmetic coding to exploit the redundancy of the high-order Markov process in the DCT domain with a few conditioning states. In addition, a context weighting technique is used to further improve the coding efficiency. The complexity of the new arithmetic coding scheme is slightly lower than that of context-based adaptive binary arithmetic coding (CABAC) of H.264. Moreover, the scheme is made compatible to the AVS baseline profile. It achieves on average 13% improvement in compression ratio over context-based two dimension variable length coding (C2DVLC) designed for the DCT domain, and a similar coding efficiency as the CABAC technique in H.264.
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.
2957878
Continuous-time equivalents of Welch bound equality sequences
The theory developed on the sequence optimization for equal-power code-division multiple-access (CDMA) systems is generalized in this paper. Unlike previous works, where discrete-time or vector channel models are predominantly employed, the overloaded channels are modeled as strictly band-limited, continuous-time multiple-access channels corrupted by additive white Gaussian noise (AWGN). After being posed as a multiple-input/single-output (MISO) joint transmitter and receiver optimization problem with the total mean-squared error (MSE) as the objective functional to be minimized, the variational problem is solved by using a frequency-domain approach. It is shown that there exist continuous-time equivalents of Welch bound equality (CTE-WBE) sequences as the jointly optimum transmit waveforms and that the matched filters are the jointly optimum receivers. The user capacity of the band-limited channels is characterized by a necessary and sufficient condition for the admissibility of users into the system in terms of the channel load, the received signal-to-noise ratio, and the signal-to-interference-plus-noise ratio (SINR) requirement. It is also shown that CTE-WBE sequences achieve the lower bound on the continuous-time equivalent of total squared correlation (CTE-TSC).
20072384
A Backward-Compatible Solution for Next Generation DVB-C System
In this paper, we propose hierarchical modulation as a backward compatible solution for next generation digital video broadcasting over cables (DVB-C2). Without modifying the architecture of legacy receivers, supplementary data can be transmitted via an added layer superimposed onto the legacy layer, and the resultant increase of transmission power is only a small fraction of that used by the legacy system. To obtain the upper bounds for the achievable throughputs, the modulation constrained capacities are derived for this layered transmission scheme. We formulate the hierarchical constellation design as a nonlinear optimization problem and then solve it through a simplified numerical method, which searches for the appropriate power allocation ratio in one-dimension space. Finally, to examine the inter-operability of channel encoder/decoder between DVB-S2 and DVB-C2, we investigate the error performance of the proposed scheme employing the LDPC codes given by DVB-S2 standard.
7527642
Spectrum Sensing for OFDM Systems Employing Pilot Tones and Application to DVB-T OFDM
Spectrum sensing is one of the core technologies of cognitive radio (CR) systems which provide a viable solution to the problem of sparsity of wireless spectrum. Nowadays, OFDM techniques are adopted by many existing or progressing wireless communication standards. Thus, a robust spectrum sensing algorithm for OFDM modulated signals is highly desired to implement CR when the primary signal uses OFDM modulation. Motivated by this demand, a time-domain symbol cross-correlation based spectrum sensing algorithm (TDSC method) is presented in this paper. The algorithm makes use of the property that the mean of the TDSC of two OFDM symbols is not zero if they have embedded the same frequency-domain pilot tones. The statistical behavior of the proposed spectrum sensor is explicitly analyzed and a theoretical lower bound on the misdetection probability is derived in this paper. An intuitive spectrum sensing method which utilizes the cyclic prefix nature of the OFDM modulated signals (CP method) is also described in this paper as a reference for comparison. Finally, we use the DVB-T Standard [8] as an application example to illustrate the proposed spectrum sensing algorithm. The simulated channel environments are the Ricean and Rayleigh channels defined in the DVB-T Standard and the additive white Gaussian noise (AWGN) channel. Four CP ratios defined in the DVB-T Standard are simulated for the probability of false alarm equaling 0.01 and the sensing time set equal to 50 ms. Simulation results show that the TDSC method can achieve a misdetection probability of 0.1 when the SNR equals -20.5 dB for all four CP ratios. The TDSC method outperforms the CP method in all cases. Furthermore, the proposed method has approximately the same detection performance for different CP ratios while the detection performance of the CP method degrades dramatically when the CP ratio becomes small. Results also reveal that the simulated performance is very close to the theoretical lower bound indicating that the lower bound can be used as a good prediction of performance.
8940979
Signature Based Spectrum Sensing Algorithms for IEEE 802.22 WRAN
Spectral sensing for the presence of ATSC DTV signals in VHF/UHF TV bands under a very low SNR environment is one of the core technologies in IEEE 802.22 WRAN. There are multiple signatures embedded in the ATSC DTV signals and these signatures can be utilized to perform spectrum sensing. Signature-based spectrum sensing algorithms have an advantage in that when the signals other than noise are detected, we are almost sure that they are signals we want to detect. Thus, in this paper, several signature based spectrum sensing algorithms are presented. The false alarm rate for detectors employing different algorithms is analytically derived. The operating characteristic curves for different detectors are determined from computer simulations using ATSC A/74 DTV signal captures as a test database.
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.