nils-herrmann/clean_scirepeval huggingface dataset:
2-dimensional motion-analysis in object-oriented coding

This paper describes a motion analysis algorithm in the object-oriented coding for video sequences and objects in the two consecutive frames of the video sequence are assumed to have moved in translational motion only. It incorporates the knowledge of the border coding process which exploits the temporal redundancies between successive image frames. After segmentation, the boundary information of an object can be obtained by employing a chain-coding technique and then this information is used to estimate the motion in the video sequences. Unlike the conventional scheme, our proposed method calculates individual sets of the mapping parameters for each object requiring motion compensation after segmentation.
A Co-Saliency Model of Image Pairs

In this paper, we introduce a method to detect co-saliency from an image pair that may have some objects in common. The co-saliency is modeled as a linear combination of the single-image saliency map (SISM) and the multi-image saliency map (MISM). The first term is designed to describe the local attention, which is computed by using three saliency detection techniques available in literature. To compute the MISM, a co-multilayer graph is constructed by dividing the image pair into a spatial pyramid representation. Each node in the graph is described by two types of visual descriptors, which are extracted from a representation of some aspects of local appearance, e.g., color and texture properties. In order to evaluate the similarity between two nodes, we employ a normalized single-pair SimRank algorithm to compute the similarity score. Experimental evaluation on a number of image pairs demonstrates the good performance of the proposed method on the co-saliency detection task.
Implementation of H.264 on Mobile Device

This paper introduces the performance and technical features of the new generation international video coding standard H.264, as well as discusses the implementation and optimization of H.264 on mobile device. Our work is to implement H.264 Baseline Projile encoder and decoder on an HP IPAQ hx4700 PDA (Personal Digital Assistant) which has a powerful embedded processor PXA27x produced by Intel. By using the way of system optimization, algorithm optimization and instruction optimization, we have successfully implemented the H.264 codec on mobile device and made great improvement in terms of coding speed with very little performance degradation in terms of PSNR and bit-rate. Experimental results show that the speed of our codec increases significantly after optimization (much more than 25 frames per second). In the QCIF (176times144) resolution, our codec can run in real time on the mobile device. Based on our optimized real-time H.264 codec, a wireless video conferencing system is implemented and is described in this paper.
A Rate and Distortion Analysis of Multiscale Binary Shape Coding Based on Statistical Learning

In this paper, we propose a statistical learning-based approach to analyze the rate-distortion characteristics of MPEG-4 multiscale binary shape coding. We employ the polynomial kernel function and epsiv-insensitive loss function for our support vector regression. To improve the accuracy of the estimation, rate and distortion related features are incorporated in the statistical learning framework. Our experimental results show that the proposed approach can achieve good performance, e.g., modelling the rate-distortion curves accurately.
Enhancement Techniques for Intra Block Matching

The intra prediction techniques employed in H.264 predict the intensities of the pixels of the current block from the neighboring pixels. Coding of intra slices requires a large number of bits. Therefore, to improve the coding efficiency, another intra prediction technique is applied with several proposed enhancement techniques including best match prediction, multiple best matches, novel padding method, skip mode, etc. Experimental results show that the coding efficiency can be improved significantly, and more than 1 dB and 0.6 dB gain in PSNR can be achieved for intra and hybrid coding, respectively.
Composite Model-Based DC Dithering for Suppressing Contour Artifacts in Decompressed Video

Because of the outstanding contribution in improving compression efficiency, block-based quantization has been widely accepted in state-of-the-art image/video coding standards. However, false contour artifacts are introduced, which result in reducing the fidelity of the decoded image/video especially in terms of subjective quality. In this paper, a block-based decontouring method is proposed to reduce the false contour artifacts in the decoded image/video by automatically dithering its direct current (DC) value according to a composite model established between gradient smoothness and block-edge smoothness. Feature points on the model with the corresponding criteria in suppressing contour artifacts are compared to show a good consistency between the model and the actual processing effects. Discrete cosine transform (DCT)-based block level contour artifacts detection mechanism ensures the blocks within the texture region are not affected by the DC dithering. Both the implementation method and the algorithm complexity are analyzed to present the feasibility in integrating the proposed method into an existing video decoder on an embedded platform or system-on-chip (SoC). Experimental results demonstrate the effectiveness of the proposed method both in terms of subjective quality and processing complexity in comparison with the previous methods.
Towards Rate-Distortion Tradeoff in Real-Time Color Video Coding

In this paper, we address the key problem in real-time video coding, the rate-distortion (R-D) tradeoff. As most video coding applications employ color images, we analyze the R-D modeling problem of the color image sequence. We investigate that the R-D characteristics of color video signal in traditional transform-based video coding systems should be modeled for the luminance and chrominance components separately. So we propose separable R-D models for color video coding. The feedback from the encoder buffer is analyzed by a control-theoretic adaptation approach to avoid buffer overflow and underflow. To achieve smooth video quality and satisfy the delay constraints in real-time applications, a novel R-D tradeoff controller is designed. In the proposed R-D tradeoff framework, both the quality variation and buffer safety are considered. Extensive simulation results demonstrate that the proposed approach can achieve smooth video quality without sacrificing overall quality while efficiently utilize the bandwidth without buffer overflow or underflow
Video Quality Assessment based on Adaptive Block-size Transform Just-Noticeable Difference model

In this paper, we propose a full reference Video Quality Assessment (VQA) algorithm based on the Adaptive Block-size Transform Just-Noticeable Difference (ABT-JND) model. Firstly, ABT-JND is introduced for its efficiency of modeling the Human Vision System (HVS) characteristics. Based on the ABT-JND model, the full reference VQA is developed, by capturing HVS responses of spatio-temporal distortions over different block-size transforms. Experimental results have demonstrated that the proposed VQA outperforms other VQA methods, while slightly poorer than MOVIE. However, it maintains a very simple formulation. Since the proposed VQA performs on transform domain, it could be easily applied on many related applications, such as video compression, watermarking, and so on.
Overview of quality assessment for visual signals and newly emerged trends

Quality assessment is not only essential on its own for testing, optimizing, benchmarking, monitoring and inspecting related systems and services, but also plays an essential role in the design of virtually all visual signal processing and communication algorithms, as well as various related decision making processes. In the paper, we provide an overview of the quality assessment approaches for traditional visual signals, as well as the newly emerged ones, which covers the subjective quality evaluation and objective quality metrics of scalable and mobile videos, high dynamic range (HDR) images, image segmentation results, 3D images/videos, and retargeted images. Also the challenges for designing effective quality metrics and corresponding applications are discussed.
Improved single video object rate control for MPEG-4

Rate control plays a central role in constant bit-rate (CBR) video coding applications using MPEG-4. The paper considers single video object (SVO) rate control for MPEG-4 and presents a new rate control algorithm based on the quadratic rate-distortion model. Based on a new measure for the encoding complexity, the constraints of the model parameter estimation and a novel quantizer control strategy are proposed. Simulation results show that the MPEG-4 coder, using the proposed algorithm, can achieve a higher PSNR than a coder using the conventional rate control algorithm.
Priority encoding of video data over ATM

We present a software prototype of a cell-loss resilient scheme for data with different priorities transmitted over ATM networks. The levels of protection provided by the scheme depend on the priority level assigned to each data segment by the user. The priority level is a function of the expected cell loss rate during transmission. The developed prototype can sustain a continuous throughput between transmitting and receiving sides at tens of kilobytes per second. Its immediate application would be useful for the real-time transmission of a scalable video stream which can be efficiently split into multilayers with different priorities.
Weakly Supervised Part Proposal Segmentation From Multiple Images.

Weakly supervised local part segmentation is challenging, due to the difficulty of modeling multiple local parts from image level prior. In this paper, we propose a new weakly supervised local part proposal segmentation method based on the observation that local parts will keep fixed along the object pose variations. Hence, the local part can be segmented by capturing object pose variations. Based on such observation, a new local part proposal segmentation model is proposed. Three aspects, such as shape similarity-based cosegmentation, shape matching-based part detection and segmentation, and graph matching-based part assignment are considered. A part segmentation energy function is first proposed. Four terms, such as MRF-based single image segmentation term, shape feature-based foreground consistency term, NCuts-based part segmentation term, and two-order graphs matching based part consistency term, are contained. Then, a three sub-minimization-based energy minimization method is proposed to accomplish approximation solution. Finally, we verify our method based on three image data sets (PASCAL VOC 2008 Part data set, UCB Bird data set, and Cat-Dog data set), and one video data set (UCF Sports) data set. The experimental results demonstrate a better segmentation performance compared with the existing object cosegmentation and part proposal generation methods.
No reference image quality metric via distortion identification and multi-channel label transfer

In this paper, we propose a no reference image quality assessment (NR-IQA) algorithm based on distortion identification (DI) and multi-channel label transfer (LT). First, the distortion type classification is used to obtain the query image's probabilities of belonging to each distortion type. Then, the distortion specific label transfer is implemented in multiple distortion category channels. Based on the hypothesis that the similar images share the similar subjective qualities, the label transfer predicts the subjective quality of the query image by pooling the labels of its k-nearest neighbors (KNN) retrieved from the annotated samples. A weighting average of the multi-channel label transfer's outputs is computed to obtain the final perceptual quality score. The weight is the query image's probability that belongs to the corresponding distortion type. The experimental results show that the proposed method outperforms representative NR-IQA approaches and some full-reference metrics.
Very low bit rate video coding using H.263 coder

Recently, ITU-T established a draft standard, H.263 to he used as a possible standard for very low bit rate video coding at less than 64 kb/s. It is based on the ITU-T H.261 standard for videoconferencing. This paper provides an analysis of the performance of H.263 coder with the aim of establishing its operational parameters and limitations when operating at very low bit rates. Its performance is then optimized by selecting the desired set of operational parameters. The H.263 coder suffers from "blocking" effects when operating at very low bit rates. To improve the subjective quality of the coded images, the discrete cosine transform (DCT) coefficients are weighted using a visual quantization matrix before quantization. Simulation results showed that the proposed method increases the peak signal-to-noise ratio (PSNR) values at all bit rates tested, but more importantly, the perceived visual quality is improved significantly by reducing the annoying "blocking" effects.
Video object segmentation using an improved level set

In this paper, we propose an improved level set method to solve the tough problem of video object segmentation. In the initialization of each frame, motion estimation compensation (MEC) is employed to evaluate the state of the object in the current frame based on the segmented result of the previous frame. To solve the error-prone at strong edge in the background, background contrast removal (BCR) method is proposed to eliminate the contrast but preserve the edge belonging to the object and background. Our method not only can totally avoid re-initialization in the process of evolution and manually initialization between successive frames but also can produce high quality segmented results in real-time. Experimental results demonstrate the effectiveness and robustness of the proposed approach on the challenging human body segmentation with the complex background.
Linear rate-distortion models for MPEG-4 shape coding

In this letter, we explore the rate-distortion (R-D) characteristics of binary shape information in the MPEG-4 standard. The shape coding scheme is a block-based context-based arithmetic encoding approach and distortion is introduced by down and up sampling. Generally, the shape bit rate and nonnormalized distortion increase in proportion with the number of border blocks. At any given resolution scale, the more complex an object, the more distortion that is introduced. Consequently, we propose an R-D model based on the parameters derived from the border blocks and a block-based shape complexity for the video object. The computational complexity is much lower than other existing methods. Experimental results show that it can accurately predict the bit rate and distortion of the binary shape for rate control purposes.
Consistent Visual Quality Control in Video Coding

Visual quality consistency is one of the most important issues in video quality assessment. When people view a sequential video, they may have an unpleasant perceptual experience if the video has an inconsistent visual quality even though the average visual quality of the video is not compromised. Thus, consistent visual quality control is mostly expected in general video encoding with limited channel bandwidth and buffer resources. However, there still has not been enough study on such an issue. In this paper, a new objective visual quality metric (VQM) is proposed first, which can easily be incorporated into video coding for guiding video coding. Second, a VQM-based window model is proposed to handle the tradeoff between visual quality consistency and buffer constraint in video coding. Third, a window-level rate control algorithm is developed to accomplish visual quality control based on the above two proposals. Finally, experimental results prove that consistent visual quality, high rate-distortion efficiency, accurate bit control, and compliant buffer constraint can be achieved by the proposed rate control algorithm.
Enhancement of image quality for low bit rate video coding

The authors propose a number of improvements based on the RM8 algorithm aimed at enhancing the visual quality of the reconstructed images, especially at the low rates of 64 and 128 kb/s. RM8 is a novel approach to defining a coding standard for video communications at p*64 kb/s. Methods studied include reducing the quantizer step size, randomized scanning of the macroblock, and/or nonuniform quantization of the transform coefficients. Reducing the quantizer step size did improve the codec performance, but only marginally. Nonuniform quantization coupled with randomized scanning of the macroblocks was found to be effective in improving the image quality, both objectively and subjectively. Improvement is particularly marked in the initial 20 frames of a sequence.
Generic Proposal Evaluator: A Lazy Learning Strategy Toward Blind Proposal Quality Assessment

Existing detection or recognition systems typically select one state-of-the-art proposal algorithm to produce massive object-covered candidate windows, and a quality metric specifically designed for this algorithm is utilized to single out small amounts of proposals. However, in practice, the accuracies of different proposal algorithms significantly change from one image content to another one. To obtain more robust proposal results, a generic proposal evaluator (GPE) is highly desired, which could choose optimal candidate windows across multiple proposal algorithms. In this paper, we propose a lazy learning strategy to train the GPE, which aims to blindly estimate the quality of each proposal without accessing to its manual annotation. Unlike the traditional end-to-end framework that learns a universal model from all training samples, we try to build query-specific training subset for each given proposal, where only its  ${k}$ -nearest-neighborhoods are collected from all labeled candidate windows. Benefits from the capability of updating the regression parameters for different visual contents, the proposed method delivers a higher quality prediction accuracy even with respect to the deep neural network learned by end-to-end method. Experimental results confirm that the proposed algorithm significantly outperforms many state-of-the-art proposal quality metrics.
Image Retargeting Quality Assessment: A Study of Subjective Scores and Objective Metrics

This paper presents the result of a recent large-scale subjective study of image retargeting quality on a collection of images generated by several representative image retargeting methods. Owning to many approaches to image retargeting that have been developed, there is a need for a diverse independent public database of the retargeted images and the corresponding subjective scores to be freely available. We build an image retargeting quality database, in which 171 retargeted images (obtained from 57 natural source images of different contents) were created by several representative image retargeting methods. And the perceptual quality of each image is subjectively rated by at least 30 viewers, meanwhile the mean opinion scores (MOS) were obtained. It is revealed that the subject viewers have arrived at a reasonable agreement on the perceptual quality of the retargeted image. Therefore, the MOS values obtained can be regarded as the ground truth for evaluating the quality metric performances. The database is made publicly available (Image Retargeting Subjective Database, [Online].  http://ivp.ee.cuhk.edu.hk/projects/demo/retargeting/index.html) to the research community in order to further research on the perceptual quality assessment of the retargeted images. Moreover, the built image retargeting database is analyzed from the perspectives of the retargeting scale, the retargeting method, and the source image content. We discuss how to retarget the images according to the scale requirement and the source image attribute information. Furthermore, several publicly available quality metrics for the retargeted images are evaluated on the built database. How to develop an effective quality metric for retargeted images is discussed through a specifically designed subjective testing process. It is demonstrated that the metric performance can be further improved, by fusing the descriptors of shape distortion and content information loss.
Error probabilities for sequency majority multiplexing in frequency-nonselective, slowly fading channels. I. Mathematical formulation

We present the mathematical formulation of a much forgotten digital multiplexing technique, sequency majority multiplexing (SMM), and outline the error probability derivations for both the SMM and the concatenated sequency majority multiplexing (CSMM) schemes. This work re-traced the steps taken in previous literature and revealed some errors reported in the reviewed papers. This paper sets the scene for the reporting of the numerical analysis on the error performance of both the SMM and CSMM schemes in both the traditional AWGN and in frequency-nonselective, slowly fading channels.
Cell-loss concealment techniques for layered video codecs in an ATM network

A layered video coding scheme with its inherent cell loss resilience has been considered as a means for transporting reliably integrated video services over an asynchronous transfer mode (ATM) based network such as the broadband-ISDN. This paper presents some data concealment techniques that can be implemented in the coding of video data at the encoder, in the ATM adaptation layer (AAL) functionality of network realization and at the decoder to improve the performance of a layered codec under different conditions of video packet loss. The performance of these techniques are verified by software simulations.
Hybrid 3D subband-predictive VQ coder for VLBR applications

A dual-mode 3D based subband video coder operating at very low bit rates for PSTN and mobile networks, is proposed. When operating in baseline mode, the input video sequence is coded using a hybrid SIM3 algorithm. In 3D mode, the encoder performed subband temporal-spatial analysis using a short length QMF filter on the motion compensated frame difference frames and the resulting subbands are vector quantized using different constrained techniques. Histogram studies and modelling are also performed on the subbands and codebooks are designed according to known source distribution. Simulation results are presented at 19.2 kbit/s at 5 frame/s on QCIF format videoconferencing and videotelephony type of sequences. Subjective evaluation revealed that the annoying 'blocking' artifacts are not visible when operating in 3D mode. In addition, due to its dual-mode capability, it also performed better than SIM3 both objectively and subjectively during period of aggressive scene changes.<<ETX>>
Objective quality assessment of image retargeting based on line distortion

With the proliferation of mobile devices, research on image retargeting is becoming ever more important. However, there is little work on image retargeting quality assessment despite its importance. In this work, we focus on evaluating retargeting quality based on line distortion. Generally, image retargeting results in content loss and shape distortion. Line segments, which are fundamental image structures, are hence discarded or distorted in retargeted images. As a result, we formulate a retargeting quality index consisted of three line distortion measures: line loss, line artifact and line rotation. To test its performance, we have validated it on the public dataset RetargetMe. Experimental results demonstrate that our method outperforms many existent ones and line distortion is a good indicator of retargeting quality.