nils-herrmann/clean_scirepeval huggingface dataset:
Rate-distortion optimized transform for intra-frame coding

In this paper, a novel algorithm is proposed for intra-frame coding, named as rate-distortion optimized transform (RDOT). Unlike existing intra-frame coding schemes where the transform matrices are either fixed or mode dependent, in the proposed algorithm, transform is implemented with multiple candidate transform matrices. With this flexibility, for coding each residual block, the encoder is endowed with the power to select the optimal transform matrix in terms of rate-distortion tradeoff. The proposed algorithm has been implemented in the latest ITU-T VCEG-KTA software. Experimental results show that, over a wide range of test set, the proposed method achieves average 0.43dB coding gain compared with the recent Mode-Dependent Directional Transform (MDDT). The improvement is more significant at high bit-rates, and up to 1dB coding gain can be achieved.
Gradual Tax Policies for China's E-commerce Based on Mode Classification

Along with the rapid development of Internet, e-commerce trade increases sharply. Whether taxes should be imposed and tax policies become the focus of attention. This paper concludes the differences of tax polices in US, EU and India by comparing them, summarizes the development of China’s e-commerce by analyzing the proportions of different modes in e-commerce transaction. From the causal analysis of differences in different countries and summary of China’s e-commerce, this paper proposes tax policies suitable for China E-commerce-Gradual Tax Policies.
A continuous Chinese sign language recognition system

We describe a system for recognizing both the isolated and continuous Chinese sign language (CSL) using two cybergloves and two 3SAPCE-position trackers as gesture input devices. To get robust gesture features, each joint-angle collected by cybergloves is normalized. The relative position and orientation of the left hand to those of the right hand are proposed as the signer position-independent features. To speed up the recognition process, fast match and frame prediction techniques are proposed. To tackle the epenthesis movement problem, context-dependent models are obtained by the dynamic programming (DP) technique. HMM are utilized to model basic word units. Then we describe training techniques of the bigram language model and the search algorithm used in our baseline system. The baseline system converts sentence level gestures into synthesis speech and gestures of a 3D virtual human synchronously. Experiments show that these techniques are efficient both in recognition speed and recognition performance.
Deinterlacing Using Hierarchical Motion Analysis

A motion-compensated deinterlacing scheme based on hierarchical motion analysis is presented. According to deinterlacing steps, our contribution can be divided into four parts: motion estimation, motion state analysis, motion consistency analysis, and finer-grained interpolation. In motion estimation, we introduce a Gaussian noise model for choosing the best motion vector for each block, and make a tradeoff between utilizing previous de-interlaced frames and avoiding error propagation. A directional interpolation method is also introduced in this part for backward fields. In motion state analysis, we define two motion states for each pixel, thus achieve a compromise between traditional block-based strategies and the extreme pixel-based case. In motion consistency analysis, we propose to measure both the motion vector consistency and the motion state consistency in order to determine whether the previous two parts should be performed again with a different block size. In finer-grained interpolation, we utilize a combination of recursive median filters to generate the final results. Experimental results show that all of the proposed techniques are effective, either objectively or subjectively. As a result, we can achieve much higher image quality, with an average gain of about 1.83 dB in terms of peak signal-to-noise ratio. Moreover, the increased computation complexity is marginal.
A flexible and high-performance hardware video encoder architecture

This paper presents a new video encoder architecture for H.264 and AVS, which adopts a novel macroblock (MB) encoding order. As a replacement of Level C+ zigzag coding order, the so-called Level C+ slash scan coding order with NOP insertion is used as MB scheduling to remove MB-level data dependency of the pipeline so that the left MB's coded results such as motion vector (MV) and reconstructed pixels can be obtained early in motion estimation (ME) stages. As a result, by sharing the reconstruction (REC) loop, sequential intra prediction (INTRA) can be split into multiple pipeline stages to explore more block-level parallelization and rate distortion optimization (RDO) based mode decision is apt to implement. The exact MV predictors (MVP) obtained in motion estimation can not only improve coding performance but also make pre-skip ME algorithm able to be applied into this architecture for low power applications. Since the proposed scheme is attributed to Level C+ data reuse, the bandwidth is decreased greatly. A real-time high-definition (HD) 1080P AVS encoder implementation on FPGA verification board with search range [-128, 128]×[-96, 96] and two reference frames at an operating frequency of 160 MHz validates the efficiency of proposed architecture.
Automatic moving object extraction in MPEG video

In this paper, we propose a moving object extraction technique for MPEG coded data directly. It is a change-based motion object extraction approach, which discriminates background and moving objects by means of the higher-order statistics (HOS) performed on the interframe differences of DC image. The DC image is partly decoded picture from the compressed video for the rapid reconstruction of image data. In order to employ an optimal threshold in moving object detection stage, the background is detected by the Moment-preserving thresholding technique for each frame. Based on the background statistic, the proportion of background variance is employed to extract the final object mask by comparison with the fourth moment measure and the variance. Experimental results have demonstrated that the proposed approach worked efficiently and showed a robust result for object extraction in compressed video.
Lagrange multiplier based perceptual optimization for high efficiency video coding

In this paper, a Lagrange multiplier based perceptual optimization scheme is proposed for high efficiency video coding (HEVC). Firstly, we propose a non-linear adjustment scheme for the Lagrange multiplier based on the specialized coding structure of HEVC and human visual system (HVS) characteristic. Then the Lagrange multiplier is incorporated into the rate distortion optimization for mode decision. Experimental results demonstrate the proposed scheme can significantly improve the subjective video quality. Compared to the HM anchor, the maximum subjective quality improvement can be up to 30% and the average subjective performance improvement is over 7%, 11% and 10% for random access, low delay P and low delay B testing configurations respectively.
Rate control for advance video coding (AVC) standard

Rate control plays a very important role in constant bit rate (CBR) coding. AVC standard is jointly developed by ISO and ITU-T, which contains several inter and intra prediction modes. Rate distortion optimization (RDO) based on prerequisite quantization parameters determines the optimal prediction of each macroblock. This makes the current AVC software difficult to adopt the existing rate control techniques. This paper proposes an efficient rate control algorithm at macroblock level for AVC standard by considering both rate control and optimal prediction selection. Firstly, a quantization parameter estimated from neighboring macroblock is used in selecting an initial prediction and calculating the activity. Secondly, the estimated quantization parameter is refined according to the activity and virtual buffer occupancy. At last, the prediction mode is determined with the refined quantization parameter. Experimental results show that the proposed rate control algorithm can accurately achieve the target bit rate. Furthermore, the coding efficiency is similar to or even better than that of variable bit rate (VBR) coding.
Application research on using geogrid in semi-filling and semi-excavating roadbed engineering

The limit equilibrium method is usually used in stability analysis of reinforced roadbed. It considers the function of reinforcing material as equivalent tension and neglects Interaction betweens oil and reinforcing material. Based on the roadbed engineering construction of phase III engineering in Beijing-Chengde Highway, a grid-soil contact element has been constructed to research the application of geogrid in semi-filling and semi-excavating roadbed, and the failure mode and stability of roadbed according to the numerical simulation result is also discussed in this study. We put forward the optimization scheme of reinforcement of using geogrid in semi-filling and semi-excavating roadbed engineering.
Complexity-Constrained H.264 Video Encoding

In this paper, a joint complexity-distortion optimization approach is proposed for real-time H.264 video encoding under the power-constrained environment. The power consumption is first translated to the encoding computation costs measured by the number of scaled computation units consumed by basic operations. The solved problem is then specified to be the allocation and utilization of the computational resources. A computation allocation model (CAM) with virtual computation buffers is proposed to optimally allocate the computational resources to each video frame. In particular, the proposed CAM and the traditional hypothetical reference decoder model have the same temporal phase in operations. Further, to fully utilize the allocated computational resources, complexity-configurable motion estimation (CAME) and complexity-configurable mode decision (CAMD) algorithms are proposed for H.264 video encoding. In particular, the CAME is performed to select the path of motion search at the frame level, and the CAMD is performed to select the order of mode search at the macroblock level. Based on the hierarchical adjusting approach, the adaptive allocation of computational resources and the fine scalability of complexity control can be achieved.
Improved intra boundary filters for HEVC

This paper presents a group of novel intra boundary filters to refine the intra prediction blocks. The existing intra boundary filters only adjust prediction blocks for a few special intra modes. While the proposed method extends the boundary filtering to all intra modes, and allows to modify up to 6 rows and columns at the boundaries of intra prediction blocks. A group of filters are designed by comprehensively considering the spatial similarity between reference samples and predicted pixels, as well as the statistical characters of boundary prediction distortion. In addition, low computational complexity is also essential to make the proposed filters simple and effective. By involving the proposed boundary filters to revise the intra prediction blocks, better prediction results can be achieved. The proposed method is implemented on top of the H.265/HEVC reference software (HM-16.12), and the experimental results show that 1.0% (up to 1.5%) BD-rate reduction is achieved under All Intra (AI) configuration.
PKUBench: A context rich mobile visual search benchmark

While there are ever growing focuses on mobile visual search in recent years, a comprehensive benchmark database with rich context information (such as GPS) for fair evaluation among different strategies is still missing. This paper introduces a PKUBench benchmark for the quantitative evaluations of mobile visual search with the support of GPS. It contains 13,179 images organized into 198 distinct landmark locations within the Peking University campus. Each location is captured with multiple shot sizes and viewing angles, using both digital cameras and phone cameras, each photo being tagged with rich contextual information in the mobile scenario. Moreover, this benchmark studies typical quality degeneration scenarios in mobile photographing, including variable resolutions, blurring, lighting changes, occlusions, as well as various viewing angles. Together with this benchmark, we provide the bag-of-visual-words search baselines involving contextual information refinement. Finally, distrac-tor images are further introduced to evaluate the robustness of visual search methods in this database.
Asymmetric circular projection for dynamic virtual reality video stream switching

To provide full panoramic video content, the transmission bandwidth and playing complexity of virtual reality (VR) video are much higher than that of traditional video. Dynamic stream switching is an efficient scheme which stores multiple asymmetric projections of panoramic video in server side, and transmits only one asymmetric projection (with much lower resolution than full panoramic video) according to the direction of user's head. In this paper, we propose an asymmetric circular (ASC) projection method to generate the asymmetric projection of panoramic video. ASC uses equal area projection in the main viewpoint area to ensure the high and uniform quality of this area, and a projection with decreasing sampling density in other areas. Experimental results show that the bit rate and playing complexity of VR video are greatly reduced with the proposed ASC method. ASC is superior to state-of-the-art method and has been adopted in the standard of IEEE 1857.9-Immersive Visual Content Coding.
Interacting Tracklets for Multi-Object Tracking

In this paper, we propose to exploit the interactions between non-associable tracklets to facilitate multi-object tracking. We introduce two types of tracklet interactions, close interaction and distant interaction. The close interaction imposes physical constraints between two temporally overlapping tracklets, and more importantly, allows us to learn local classifiers to distinguish targets that are close to each other in the spatiotemporal domain. The distant interaction, on the other hand, accounts for the higher order motion and appearance consistency between two temporally isolated tracklets. Our approach is modeled as a binary labeling problem and solved using the efficient quadratic pseudo-Boolean optimization. It yields promising tracking performance on the challenging PETS09 and MOT16 dataset.
A study on interest point guided visual saliency

Visual attention is one of the most critical characteristics of human visual system (HVS), which infers the attractive regions in a visual scene. It has been an active research topic over the past decades and many proposed models of visual attention have demonstrated successful applications in a wide range of fields including computer vision and image processing. On the other hand, interest point detection is another hot topic that leads practical contributions to the real-time applications such as visual retrieval and augmented reality. In this paper, we try to investigate the relationship between the interest point and the visual attention. An informative analysis is reported by comparing the performance of different interest point models in predicting the visual fixation. It is found that the blob based interest point model generally outperforms the corner based model. Furthermore, we propose a mixture strategy by integrating all the interest point algorithms, and the experimental results indicate that this proposed method is competitive with some state-of-the-art algorithms.
Reduced reference image quality assessment using entropy of primitives

In this paper, we propose a new reduced reference image quality assessment algorithm based on the recent advances in sparse coding and representation, particularly, the entropy of primitives (EoP). The EoP is defined in terms of the distribution of the primitives, which form an overcomplete dictionary to represent the natural scene by linear combination. Constructively, we develop a reduced reference EoP based distortion metric (EoPM). EoPM has the property that it is nearly invariant to the geometry distortions, which hardly affect the visual quality but are often wrongly predicted by the existing image quality assessment metrics with severe distortion. Experimental results show that the accuracy of EoPM is highly competitive to the popular reduced reference image quality assessment algorithm on the public dataset.
Cost-volume filtering-based stereo matching with improved matching cost and secondary refinement

Recent cost-volume filtering-based local stereo methods have achieved comparable accuracy with global methods. However, there are still some significant outliers existing in the final disparity map. In this paper, we propose a cost-volume filtering-based local stereo matching method that employs a new combined cost and a novel secondary disparity refinement mechanism. The combined cost is formulated by a modified color census transform, truncated absolute differences of color and gradients. Symmetric guided filter is used for the cost aggregation. Different from traditional stereo matching, a novel secondary disparity refinement is proposed to further remove remaining outliers. Experimental results on Mid-dlebury benchmark show that our method ranks the 5th out of the 144 submitted methods, and is the best cost-volume filtering-based local method. Furthermore, experiments on real world sequences also validate the effectiveness of our proposed method.
Content adaptive in-loop depth map filter for HEVC based 3DV coding

In this paper, a content adaptive in-loop depth map filter is proposed for HEVC based 3DV video coding to improve the quality of the synthesized views. The proposed depth map filtering scheme is block based by reusing the TU (transform unit) split structure in HEVC. Firstly, TU are classified into 3 categories: flat, directional, and textureless, according to the characteristics of the depth map. Then four kinds of filters are designed by considering the characteristics of the current TU and neighbor TUs jointly. The proposed scheme is incorporated into HTM3.0- the reference software of HEVC based 3D video coding. The experimental results show both subjective and objective quality improvement. The average BD-rate reduction is 0.65% for synthesis views in HD test sequences, and the maximum BD-rate reduction is up to 1.6%.
Data-based affinity analysis of power transformer defects with adaptive frequent itemset mining algorithm

In worldwide power market, intelligent assessment techniques for power transformers are continuously necessitated to deal with the issues of aging apparatus, upgraded power networks, market deregulation, etc. Considering the disadvantage of subjective judgement with regard to the current assessment systems, data-based analysis approaches (e.g. big data and machine learning techniques) are intended to apply into condition assessment of power apparatus. The database related to power transformers needs multistage processes. The dataset thereof, which relates to familial defects, is considered containing valuable information for condition assessment of power transformers. Affinity analysis can help to mine this type of information. To perform the affinity analysis, this study presents a novel adaptive frequent itemset mining algorithm which is developed based on Apriori algorithm. This algorithm is proposed to meet the specific requirements of mining the familial defect information, thereby supporting an intelligent condition assessment system of power transformers. 11,266 real records from in-service power transformers are used to implement the affinity analysis. The results can quantitatively indicate the affinity among manufacturers, operating years, voltage grades of transformers and their defective parts.
Arithmetic coding with improved solution for the carry-over problem

The carry-over problem is inherent in arithmetic coding as a result of using finite precision arithmetic. As far as we know, the currently widely used solution for this problem is the bit-stuffing technique, which was proposed by Rissanen and Langdon (198l). However, this technique is not completely satisfactory. The stuffed-bit affects the coding efficiency slightly. The code stream inserted with several stuffed-bits loses its concept as a real number. This conflicts with the principle that arithmetic coding maps an input stream to an interval on the real line, which is neither perfect nor convenient for analysis. We present our solution for the carry-over problem, the carry-trap technique, which works without the deliberately inserted stuffed-bit. We also present a concise termination method, named the medium termination technique. Both are proved rigorously.
Joint Chroma Downsampling and Upsampling for Screen Content Image

Screen content images are originally captured in a full-chroma format. The chroma downsampling, which is commonly applied to the chroma component in screen content image representation and processing (e.g., YUV4:2:0 compression), will significantly degrade the image quality and create annoying artifacts such as blur and color shifting. To tackle this problem, in this paper we propose luma aware chroma downsampling and upsampling algorithms to jointly improve the quality of the chroma image reconstruction. Guided by the luma information, the chroma upsampling algorithm is proposed with the utilization of major color and index map representation. The geometric information-based linear mapping is developed to transfer the structure of luma to the interpolated chroma. Subsequently, the error sensitivity of the upsampling method is analyzed, and content dependent downsampling algorithm is presented to minimize the error sensitivity function. We further explore the applicability of the proposed scheme in the scenario of screen content compression, targeting at improving the decoded chroma image quality for display. Extensive experimental results demonstrate the viability and efficiency of the proposed scheme.
New scaling technique for direct mode coding in B pictures

To leave the maximum flexibility in encoder to optimize the trade-off between coding performance and complexity, in video coding standards such as H.264 AVC, H.263 and MPEG-4 etc, any number of B pictures and any arrangement of P pictures within a group of pictures (GOP) of arbitrary length are permitted. In addition, multiple reference picture prediction is also permitted in some video coding systems such as H.264/AVC to achieve efficient coding by allowing the encoder to select reference pictures among a large number of coded pictures. Both of the above cases without fixing the temporal distance between forward and backward reference pictures require the division operation for deriving the motion vectors of direct mode, which can efficiently exploit the temporal correlation among pictures and does not require any bits for coding the motion vectors. However, the division is an expensive and undesired operation in video decoder hardware design. Although the H.264/AVC video standard has provided a scaling technique to tackle this problem, unfortunately, its performance is also deteriorated. This paper presents a new scaling technique to both remove the division operation for deriving direct mode motion vectors and efficiently improve the accuracy of derived direct mode motion vectors compared with the scaling technique in H.264/AVC.
Building IPsec VPN in IPv6 Based on Openswan

This paper researches and analyses feature and advantages of IPsec VPN, points out its problem and disadvantages in the IPv4. After analyzing IPv6 network and its data package in deep, this paper studies the feasibility of implementation of IPsec VPN in IPv6 network. Then it elaborates frame and modules which supports IPv6 of Openswan. Via recompiling the 2.6 kernel, adding the NETKEY module to kernel, installing Openswan and configuring it, a IPsec VPN which can runs in pure IPv6 network has been built. Finally, function and performance testing is done.