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.
8954904
Modification of the AdaBoost-based Detector for Partially Occluded Faces
While face detection seems a solved problem under general conditions, most state-of-the-art systems degrade rapidly when faces are partially occluded by other objects. This paper presents a solution to detect partially occluded faces by reasonably modifying the AdaBoost-based face detector. Our basic idea is that the weak classifiers in the AdaBoost-based face detector, each corresponding to a Haar-like feature, are inherently a patch-based model. Therefore, one can divide the whole face region into multiple patches, and map those weak classifiers to the patches. The weak classifiers belonging to each patch are re-formed to be a new classifier to determine if it is a valid face patch - without occlusion. Finally, we combine all of the valid face patches by assigning the patches with different weights to make the final decision whether the input subwindow is a face. The experimental results show that the proposed method is promising for the detection of occluded faces
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.
18296363
A Real-Time Score Detection and Recognition Approach for Broadcast Basketball Video
For broadcast sports video, score information is an effective mid-level representation to facilitate high-level video content analysis. In this paper, we propose a real-time approach to detect score region and recognize scores in broadcast basketball video. First, score region is automatically detected using frame difference and texture information without any prior knowledge. Then, score digit is recognized using a coarse-to-fine scheme based on score spatial structure, temporal correlation and changing rules. Compared with traditional video text recognition method, our approach is computing-insensitive and independent of digit model training. Experimental results show that our approach achieves real-time performance and is robust for the variation of digit font, size, color and noise caused by low frame resolution in broadcast basketball video.
37403020
Contour-motion feature (CMF): A space-time approach for robust pedestrian detection
This paper presents a contour-motion feature for robust pedestrian detection. The space-time contours are used as the low level representation of the pedestrian. Then we apply 3D distance transform to extend the 1-dimensional contour into 3-dimensional space. By this way, the relations between the local contours can be maintained implicitly. Further, by encapsulating the static and dynamic information by 3D Haar-like filters, we can generate the middle level pedestrian representation: contour-motion features. Then we use boosting method to select the most representative features. Our experiments demonstrate that the proposed approach can outperform Viola's well-known pedestrian detector in both detection accuracy and generalization ability. In addition, even though our approach is presented in pedestrian detection scenario, it has been extended to human activity recognition application and remarkable performance has been achieved.
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.
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.
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.
14749080
Mobile Robot Sonar Backscatter Algorithm for Automatically Distinguishing Walls, Fences, and Hedges
We present an algorithm to distinguish several types of brick walls, picket fences, and hedges based on the analysis of backscattered sonar echoes. The echo data are acquired by a mobile robot with a single-transducer 50 kHz pulse-echo sonar computer-controlled scanning system packaged as its sensor head. For several locations along a wall, fence, or hedge, a fan of backscatter sonar echoes is acquired, digitized, and stored on a computer as the sonar transducer is swept over a horizontal arc. Off-line, each digitized echo waveform is then rectified, smoothed, and summed to give a measure of the backscatter strength. This backscatter is then plotted versus scan angle, with a series of N-peak deformable templates fit to these data for each scan. The number of peaks in the best-fitting N-peak template indicates the presence and location of retro-reflectors, and allows automatic categorization of the various fences, hedges, and brick walls.
17317140
A Reconfigurable High Availability Infrastructure in Cluster for Grid
The paper presents the implementation and analysis of a service-based reconfigurable High Availability infrastructure of cluster system for Grid. Based on service notion, the High Availability infrastructure is constructed for mission critical applications on Grid. The application high availability service is responsible for registered applications’ high availability. The Service Manager is in charge of monitoring all services via heartbeat and automatically recovering from failure to assure service high availability. To improve flexibility and dependability, a dynamic reconfiguration mechanism is designed so that the configurations can be changed without interrupting application’s running. A dependability modeling and simulation tool is deployed in the reconfiguration procedure. Dependability parameters can be inputted into the simulation tool. With the objects and sub-model library in the tool, corresponding global model will be constructed and statistic result for different recovery strategies is given. The configuration of application can be adjusted based on these statistic results.