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
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.
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.
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.
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.
8471073
Spectrum Sensing for DMB-T Systems Using PN Frame Headers
Spectrum sensing for the China digital television terrestrial broadcasting system is considered in this paper. The spectrum sensing algorithms utilize PN sequences embedded in the frame headers to perform spectrum sensing. A theoretical lower bound on the misdetection probability for each spectrum sensor presented in this paper is derived. The performances of the proposed spectrum sensing algorithms are demonstrated by computer simulation for the multipath Rayleigh fading and steady state multipath Rayleigh fading channels. Simulation results show that the misdetection probability evaluated by computer simulations is close to the lower bound on the misdetection probability for a steady state multipath Rayleigh channel. When the probability of false alarm is 0.01 and a 50 ms of sensing time is used, a misdetection probability equal to 0.1 is achieved when the signal to noise power ratio is -16 dB, -18.8 dB, and -18 dB for modes 1, 2, and 3 in the multipath Rayleigh fading channel, respectively.
5747221
Application Research of Design Patterns in Virtual Trade Platform
Shanxi Coal Transportation and Marketing Group Limited has abundant coal and infrastructure network resources, maturity the highway system of coal transportation. The construction of virtual trade platform can share resources, accelerate the circulation speed of resources, reduce business costs, and improve business efficiency. The paper applies design pattern to virtual trade platform. The system has the advantage of strong scalability and maintainability, easy to develop and support multiple types of user interface.
46501259
A proactive fault-detection mechanism in large-scale cluster systems
36578035
Mobile robot sonar interpretation algorithm for distinguishing trees from poles
Abstract We describe an algorithm to automatically distinguish trees from round metal poles with a sonar system packaged on a mobile robot. A polynomial interpolation of the square root of the backscattered signal energy versus scan angle is first plotted. Asymmetry and fitting error are then extracted for each sweep across the object, giving a single point in an abstract phase space. Round metal poles are nearer to the origin than are trees, which scatter the sonar more irregularly due to lobulations and/or surface roughness. Results are shown for 20 trees and 10 metal poles scanned on our campus.
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.