Abstract: For the OFDM-based Amplify-and-Forward cooperative system, a novel relay-superimposed pilot strategy is proposed, where the source pilot symbols are frequency division multiplexed to estimate the cascaded channel while relay pilot sequence is superimposed onto the top of the cooperative data stream for second-hop channel estimation. This method avoids the loss of data rate for additional pilot subcarriers but results in the interference of unknown cooperative data. To remove the interference of cooperative data during the estimation of second-hop channel, the Cooperative Interference Cancelation scheme assisted by cooperative data from direct link is proposed. We derive the approximated lower bound for the MSE of second-hop channel estimation. Simulation results are presented to validate the performance of the proposed schemes. PubDate: Thu, 01 Mar 2018 00:00:00 +000
Abstract: Quality of Experience (QoE) of video streaming services has been attracting more and more attention recently. Therefore, in this work we designed and implemented a real-time QoE monitoring system for streaming services with Adaptive Media Playout (AMP), which was implemented into the VideoLAN Client (VLC) media player to dynamically adjust the playout rate of videos according to the buffer fullness of the client buffer. The QoE monitoring system reports the QoE of streaming services in real time so that network/content providers can monitor the qualities of their services and resolve troubles immediately whenever their subscribers encounter them. Several experiments including wired and wireless streaming were conducted to show the effectiveness of the implemented AMP and QoE monitoring system. Experimental results demonstrate that AMP significantly improves the QoE of streaming services according to the Mean Opinion Score (MOS) estimated by our developed program. Additionally, some challenging issues in wireless streaming have been easily identified using the developed QoE monitoring system. PubDate: Thu, 15 Feb 2018 00:00:00 +000
Abstract: We consider the training design and channel estimation in the amplify-and-forward (AF) diamond relay network. Our strategy is to transmit the source training in time-multiplexing (TM) mode while each relay node superimposes its own relay training over the amplified received data signal without bandwidth expansion. The principal challenge is to obtain accurate channel state information (CSI) of second-hop link due to the multiaccess interference (MAI) and cooperative data interference (CDI). To maintain the orthogonality between data and training, a modified relay-assisted training scheme is proposed to migrate the CDI, where some of the cooperative data at the relay are discarded to accommodate relay training. Meanwhile, a couple of optimal zero-correlation zone (ZCZ) relay-assisted sequences are designed to avoid MAI. At the destination node, the received signals from the two relay nodes are combined to achieve spatial diversity and enhanced data reliability. The simulation results are presented to validate the performance of the proposed schemes. PubDate: Wed, 08 Nov 2017 00:00:00 +000
Abstract: Channel change time is a critical quality of experience (QOE) metric for IP-based video delivery systems such as Internet Protocol Television (IPTV). An interesting channel change acceleration scheme based on peer-assisted delivery was recently proposed, which consists of deploying one FCC server (Fast Channel Change Server) in the IP backbone in order to send the unicast stream to the STB (Set-Top Box) before sending the normal multicast stream after each channel change. However, deploying such a solution will cause high bandwidth usage in the network because of the huge unicast traffic sent by the FCC server to the STBs. In this paper, we propose a new solution to reduce the bandwidth occupancy of the unicast traffic, by deploying the FCC server capabilities on the user STB. This means that, after each channel change request, the STB will receive the unicast traffic from another STB instead of the central server. By using this method, the unicast traffic will not pass through the IP network; it will be a peer-to-peer communication via the Access Network only. Extensive simulation results are presented to demonstrate the robustness of our new solution. PubDate: Tue, 31 Oct 2017 00:00:00 +000
Abstract: We propose a novel approach for low-light image enhancement. Based on illumination-reflection model, the guided image filter is employed to extract the illumination component of the underlying image. Afterwards, we obtain the reflection component and enhance it by nonlinear functions, sigmoid and gamma, respectively. We use the first-order edge-aware constraint in the gradient domain to achieve good edge preserving features of enhanced images and to eliminate halo artefact effectively. Moreover, the resulting images have high contrast and ample details due to the enhanced illumination and reflection component. We evaluate our method by operating on a large amount of low-light images, with comparison with other popular methods. The experimental results show that our approach outperforms the others in terms of visual perception and objective evaluation. PubDate: Thu, 28 Sep 2017 00:00:00 +000
Abstract: Geometry images are a kind of completely regular remeshing methods for mesh representation. Traditional geometry images have difficulties in achieving optimal reconstruction errors and preserving manually selected geometric details, due to the limitations of parametrization methods. To solve two issues, we propose two adaptive geometry images for remeshing triangular meshes. The first scheme produces geometry images with the minimum Hausdorff error by finding the optimization direction for sampling points based on the Hausdorff distance between the original mesh and the reconstructed mesh. The second scheme produces geometry images with higher reconstruction precision over the manually selected region-of-interest of the input mesh, by increasing the number of sampling points over the region-of-interest. Experimental results show that both schemes give promising results compared with traditional parametrization-based geometry images. PubDate: Wed, 02 Aug 2017 00:00:00 +000
Abstract: With the rapid development of CT technology, especially the higher resolution of CT machine and a sharp increase in the amount of slices, to extract and three-dimensionally display aortic dissection from the huge medical image data became a challenging task. In this paper, active shape model combined with spatial continuity was adopted to realize automatic reconstruction of aortic dissection. First, we marked aortic feature points from big data sample library and registered training samples to build a statistical model. Meanwhile, gray vectors were sampled by utilizing square matrix, which set the landmarks as the center. Posture parameters of the initial shape were automatically adjusted by the method of spatial continuity between CT sequences. The contrast experiment proved that the proposed algorithm could realize accurate aorta segmentation without selecting the interested region, and it had higher accuracy than GVF snake algorithm (93.29% versus 87.54% on aortic arch, 94.30% versus 89.25% on descending aorta). Aortic dissection membrane was extracted via Hessian matrix and Bayesian theory. Finally, the three-dimensional visualization of the aortic dissection was completed by volume rendering based on the ray casting method to assist the doctors in clinical diagnosis, which contributed to improving the success rate of the operations. PubDate: Wed, 19 Jul 2017 07:12:01 +000
Abstract: Computer 3D character animation essentially is a product, which is combined with computer graphics and robotics, physics, mathematics, and the arts. It is based on computer hardware and graphics algorithms and related sciences rapidly developed new technologies. At present, the mainstream character animation technology is based on the artificial production of key technologies and capture frames based on the motion capture device technology. 3D character animation is widely used not only in the production of film, animation, and other commercial areas but also in virtual reality, computer-aided education, flight simulation, engineering simulation, military simulation, and other fields. In this paper, we try to study physics based character animation to solve these problems such as poor real-time interaction that appears in the character, low utilization rate, and complex production. The paper deeply studied the kinematics, dynamics technology, and production technology based on the motion data. At the same time, it analyzed ODE, PhysX, Bullet, and other variety of mainstream physics engines and studied OBB hierarchy bounding box tree, AABB hierarchical tree, and other collision detection algorithms. Finally, character animation based on ODE is implemented, which is simulation of the motion and collision process of a tricycle. PubDate: Wed, 12 Jul 2017 00:00:00 +000
Abstract: Text representation is a basic issue of text information processing and event plays an important role in text understanding; both attract the attention of scholars. The event network conceals lexical relations in events, and its edges express logical relations between events in document. However, the events and relations are extracted from event-annotated text, which makes it hard for large-scale text automatic processing. In the paper, with expanded CEC (Chinese Event Corpus) as data source, prior knowledge of manifestation rules of event and relation as the guide, we propose an event extraction method based on knowledge-based rule of event manifestation, to achieve automatic building and improve text processing performance of event network. PubDate: Sun, 04 Jun 2017 08:25:11 +000
Abstract: Recommender system is a very efficient way to deal with the problem of information overload for online users. In recent years, network based recommendation algorithms have demonstrated much better performance than the standard collaborative filtering methods. However, most of network based algorithms do not give a high enough weight to the influence of the target user’s nearest neighbors in the resource diffusion process, while a user or an object with high degree will obtain larger influence in the standard mass diffusion algorithm. In this paper, we propose a novel preferential diffusion recommendation algorithm considering the significance of the target user’s nearest neighbors and evaluate it in the three real-world data sets: MovieLens 100k, MovieLens 1M, and Epinions. Experiments results demonstrate that the novel preferential diffusion recommendation algorithm based on user’s nearest neighbors can significantly improve the recommendation accuracy and diversity. PubDate: Thu, 04 May 2017 00:00:00 +000
Abstract: Compressive-Sensing Video Coding (CSVC) is a new video coding framework based on compressive-sensing (CS) theory. This paper presents the evaluations on rate-distortion performance and rate-energy-distortion performance of CSVC by comparing it with the popular hybrid video coding standard H.264 and distributed video coding (DVC) system DISCOVER. Experimental results show that CSVC achieves a poor rate-distortion performance when compared with H.264 and DISCOVER, but its rate-energy-distortion performance has a distinct advantage; moreover, its energy consumption of coding is approximately invariant regardless of reconstruction quality. It can be concluded that, with a limited energy budget, CSVC outperforms H.264 and DISCOVER, but its rate-distortion performance still needs improvement. PubDate: Thu, 16 Mar 2017 06:20:12 +000
Abstract: The traditional image Compressive Sensing (CS) conducts block-wise sampling with the same sampling rate. However, some blocking artifacts often occur due to the varying block sparsity, leading to a low rate-distortion performance. To suppress these blocking artifacts, we propose to adaptively sample each block according to texture features in this paper. With the maximum gradient in 8-connected region of each pixel, we measure the texture variation of each pixel and then compute the texture contrast of each block. According to the distribution of texture contrast, we adaptively set the sampling rate of each block and finally build an image reconstruction model using these block texture contrasts. Experimental results show that our adaptive sampling scheme improves the rate-distortion performance of image CS compared with the existing adaptive schemes and the reconstructed images by our method achieve better visual quality. PubDate: Mon, 13 Mar 2017 00:00:00 +000
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