nils-herrmann/clean_scirepeval huggingface dataset:
Polygonizing non-uniformly distributed 3D points by advancing mesh frontiers

3D digitization devices produce very large sets of 3D points sampled from the surfaces of the objects being scanned. A mesh construction procedure needs to be applied to derive polygon mesh from the 3D point sets. As the 3D points derived from digitization devices based on digital imaging technologies are inherently non-uniformly distributed over regions that may contain surface discontinuities, existing methods are not suitable for polygonizing them. This paper describes a novel polygonization algorithm for constructing triangle mesh from unorganized 3D points. In contrast to existing methods, this algorithm begins the mesh construction process from 3D points lying on smooth surfaces, and advances the mesh frontier towards 3D points lying near surface discontinuities. If 3D points along the edges and at the corners are sampled, then the algorithm will form an edge where two advancing frontiers meet, and a corner where three or more frontiers meet. Otherwise, the algorithm constructs approximations of the edges and corners. It can be shown that this frontier advancing algorithm performs 2D Delaunay triangulation of 3D points lying on a plane in 3D space.
Video seam carving with perspective line structure preservation

When people want to transform the size of image or video into different kinds of ratio, it is possibly lost the important and significant object while doing this operation. Various strategies have been tested for achieving this issue such as seam carving. It can retain the crucial objects and remove the insignificant pixels repeatedly, resulting in the content-aware image/video. Such ordinary method presents vital problem is that it could destroy the line structure and shape of the object, which can be easily find out by the viewers. The video seam carving will also cause the continuous problem because of the motion. In this paper, we provide the state-of-the-art strategies focus on maintaining the perspective line structure in video, especially in vehicle video recorder. We also compare proposed method with the other papers. The complete experiments would be illustrated in the website http://video.minelab.tw/pl/PLseamCarving.
Knowledge-Guided Docking of Flexible Ligands to SH2 Domain Proteins

Studies of interactions between protein domains and ligands are important in many aspects such as cellular signaling and regulation. In this work, we applied a three-stage knowledge-guided approach of docking flexible peptide ligands to SH2 domains. The first stage of the approach search for binding pockets of SH2 domain proteins and binding motifs of peptide ligands based on known features. The knowledge of the binding sites are used in the second stage as binding constraints to align ligand's peptide backbone to the SH2 domain. The backbone-aligned ligands produced serve as good starting points to the third stage which uses a Monte Carlo method to perform the flexible docking. The experimental results show that the backbone alignment method at the second stage produces good backbone conformations which are close to the conformation in complex. The binding site information is well utilized to provide a better starting point to the next docking stage. The subsequent docking is successful or partially successful in 5 of 7 test cases. The performance is better than that of general docking methods. The presented approach can also be applied to other well characterized protein domains which bind ligands in two or more binding grooves.
Rain Removal in Video by Combining Temporal and Chromatic Properties

Removal of rain streaks in video is a challenging problem due to the random spatial distribution and fast motion of rain. This paper presents a new rain removal algorithm that incorporates both temporal and chromatic properties of rain in video. The temporal property states that an image pixel is never always covered by rain throughout the entire video. The chromatic property states that the changes of R, G, and B values of rain-affected pixels are approximately the same. By using both properties, the algorithm can detect and remove rain streaks in both stationary and dynamic scenes taken by stationary cameras. To handle videos taken by moving cameras, the video can be stabilized for rain removal, and destabilized to restore camera motion after rain removal. It can handle both light rain and heavy rain conditions. Experimental results show that the algorithm performs better than existing algorithms
A cognitive virtual microscopic framework for knowlege-based exploration of large microscopic images in breast cancer histopathology

Histopathological examination is a powerful method for prognosis of major diseases such as breast cancer. Analysis of medical images largely remains the work of human experts. Current virtual microscope systems are mainly an emulation of real microscopes with annotation and some image analysis capabilities. However, the lack of effective knowledge management prevents such systems from being computer-aided prognosis platforms. The cognitive virtual microscopic framework, through an extended modeling and use of medical knowledge, has the capacity to analyse histopathological images and to perform grading of breast cancer, providing pathologists with a robust and traceable second opinion.
Knowledge-Guided Semantic Indexing of Breast Cancer Histopathology Images

Narrowing the semantic gap represents one of the most outstanding challenges in medical image analysis and indexing. This paper introduces a medical knowledge - guided paradigm for semantic indexing of histopathology images, applied to breast cancer grading (BCG). Our method improves pathologists' current manual procedures consistency by employing a semantic indexing technique, according to a rule-based decision system related to Nottingham BCG system. The challenge is to move from the medical concepts/ rules related to the BCG, to the computer vision (CV) concepts and symbolic rules, to design a future generic framework- following Web Ontology Language standards - for an semi- automatic generation of CV rules. The effectiveness of this approach was experimentally validated over six breast cancer cases consisting of 7000 frames with domain knowledge from experts of Singapore National University Hospital, Pathology Department. Our method provides pathologists a robust and consistent tool for BCG and opens interesting perspectives for the semantic retrieval and visual positioning.
Recovery of 3D Pose of Bones in Single 2D X-ray Images

Estimation of the 3D pose of bones in 2D images plays an important role in computer-assisted diagnosis and surgery. Existing work has focused on registering a 3D model of the bone to the images of the same bone. This approach incurs a high health care cost on the patients, and are prescribed only for certain procedures. Such computer assistance is not routinely available to diagnostic and surgical procedures that involve only X-ray images, limiting the precision of the procedures. This paper proposes a method for recovering 3D pose by registering a generic 3D model of a bone to single X-ray images of different patients. It can perform 3D-2D registration with unknown correspondence automatically. Comprehensive test results show that the method is accurate and robust in recovering the pose of femurs in the X-ray images of different patients
Identifying painters from color profiles of skin patches in painting images

Research on digital analysis of painting images has received very little attention. The exact nature of scientific methods seems to be antithesis of art. Nevertheless, several papers have proposed methods to bridge this gap and have obtained interesting results. In fact, some art theorists have pointed out the usefulness of specific quantifiable features in the paintings. This paper presents a method for identifying painters using color profiles of skin patches in painting images. Various color models for representing the color profiles were explored. Various implementations of multiclass support vector machine classfiiers were compared. We found that a weighted combination of several directed acyclic graph SVMs with Gaussian kernels gives the best classification performance.
A hybrid model for invariant and perceptual texture mapping

Texture is an important visual feature for computer vision tasks. In applications such as image retrieval and computer image understanding, texture similarity should be measured in a manner that is invariant to texture scale and orientation, as well as consistent with human perception. However, most existing computational features and similarity measures are not perceptually consistent. A solution is to map textures into an invariant and perceptual space such that similarity measured in the space is perceptually consistent. The paper presents a hybrid method, using a convolutional neural network and SVM, to perform the invariant and perceptual mapping. Test results show that it's overall performance is better than that of an individual neural network. and a SVM.
Feature Combination and Relevance Feedback for 3D Model Retrieval

Retrieval of 3D models have attracted much research interest, and many types of shape features have been proposed. In this paper, we describe a novel approach of combining the feature types for 3D model retrieval and relevance feedback processing.Our approach performs query processing using pre-computed pairwise distances between objects measured according to various feature types. Experimental tests show that this approach performs better than retrieval by individual feature type.
Reinforcement learning for video encoder control in HEVC

In todays video compression systems, the encoder typically follows an optimization procedure to find a compressed representation of the video signal. While primary optimization criteria are bit rate and image distortion, low complexity of this procedure may also be of importance in some applications, making complexity a third objective. We approach this problem by treating the encoding procedure as a decision process in time and make it amenable to reinforcement learning. Our learning algorithm computes a strategy in a compact functional representation, which is then employed in the video encoder to control its search. By including measured execution time into the reinforcement signal with a lagrangian weight, we realize a trade-off between RD-performance and computational complexity controlled by a single parameter. Using the reference software test model (HM) of the HEVC video coding standard, we show that over half the encoding time can be saved at the same RD-performance.
Efficient coding of segmentation maps for layered object representations

In object/region-based video coding, the side information is increased by the contour information. Thus, efficient lossy contour coding algorithms have to be developed. A class of very suitable motion segmentation algorithms provide a so-called layered representation of video sequences. Algorithm for segmentation map coding of layered object representations is proposed. It exploits the temporal connectivity of object masks by a transformation into an object domain. The contour coding is done in the object domain by a wavelet-based technique. Performance investigations show that very low bit-rates can be reached.
Generalized interpolation for motion compensated prediction

Fractional sample interpolation with FIR filters is commonly used for motion compensated prediction (MCP). The FIR filtering can be viewed as a signal decomposition using restricted basis functions. The concept of generalized interpolation provides a greater degree of freedom for selecting basis functions. We implemented generalized interpolation using a combination of short IIR and FIR filters. An efficient multiplication-free design of the algorithm that is suited for hardware implementation is shown. Compared to a 6-tap FIR interpolation filter, average rate savings of 3.1% are observed. A detailed analysis of the complexity and memory bandwidth cycles compared to existing interpolation techniques for MCP is provided.
Multiview extension of HEVC using reduced resolution disparity information for inter-view prediction tools

This paper investigates the effect of reducing the resolution of estimated depth maps that are used for inter-view motion and residual prediction in a multiview extension of HEVC. The investigated HEVC extension includes disparity compensated prediction similar to the MVC extension of H.264/AVC. For further increasing the coding efficiency, the obtained disparity vectors are used to estimate depth maps, which are employed by two additional tools: The inter-view motion prediction uses the estimated data for predicting motion vectors of dependent views from the independent view while the inter-view residual prediction uses the depth data for predicting the residual data of dependent views. Simulations showed that, on average, bit rate savings of about 10% for the dependent views are achieved by enabling the additional coding tools. By reducing the resolution of the estimated depth maps, the decoding complexity overhead associated with the inter-view motion and residual prediction can be significantly decreased from about 167% to 128% at the expense of a minor bit rate increase of about 0.5%.
Encoder control for renderable regions in high efficiency multiview video plus depth coding

This paper describes a new encoder control method for multiview video plus depth coding. Since large parts of a multiview scenery are present in more than one of the captured video sequences, a depth-aware encoder control is introduced, which identifies those regions based on given depth maps and omits the coding of the residual signal for those regions. Experimental results indicate that bit rate reductions of about 5-9 %, depending on the bit rate, can be achieved for the 2-view case at a constant subjective quality.
Multi-frame optimized quantization for high efficiency video coding

In video coding, the coding decisions made during the encoding of a reference frame impact the achievable rate distortion performance of all inter-predicted frames which refer to it. Most encoders operate frame-by-frame and do not specifically consider this inter-dependency. In this paper, a multi-frame transform coefficient optimization method for H.265/HEVC is proposed. The inter-frame dependencies are described using a linear signal model, such that the optimization problem can be cast in the form of an ℓ1-regularized least squares problem. A simple functional relationship between the regularization parameter and the quantization paramter is empirically found. Bit rate savings are in the range of 7-10% for a simple IPPP... prediction structure and about 3% for a random access configuration.
Video coding with cubic spline interpolation and adaptive motion model selection

We propose a block based video coder with multiple motion models. The coder is designed such that each block can be predicted using the motion model with the best rate-distortion performance. In such a scheme, there is a significant impact on the interpolation, motion compensated prediction structure and the design of motion vector predictors, because neighboring blocks could have been predicted by different models. We employ cubic splines to perform interpolation and use the spline framework to estimate the translational shift and warping of blocks. We address the problem of adaptive model selection and enhance the motion vector predictors to account for multiple motion models. Bitrate savings up to 11.7% are observed for the tested sequences compared to an improved H.264/AVC reference.
3D video coding using the synthesized view distortion change

In 3D video, texture and supplementary depth data are coded to enable the interpolation of a required number of synthesized views for multi-view displays in the range of the original camera views. The coding of the depth data can be improved by analyzing the distortion of synthesized video views instead of the depth map distortion. Therefore, this paper introduces a new distortion metric for 3D video coding, which relates changes in the depth map directly to changes of the overall synthesized view distortion. It is shown how the new metric can be integrated into the rate-distortion optimization (RDO) process of an encoder, that is based on high-efficiency video coding technology. An evaluation of the modified encoder is conducted using different view synthesis algorithms and shows about 50% rate savings for the depth data or 0.6 dB PSNR gains for the synthesized view.
Inter-view prediction of motion data in multiview video coding

A new method for increasing the coding efficiency of dependent views in multiview video coding by employing already coded motion parameters of other views is presented. The correspondence between a block in a dependent view and a block in a reference view is established by estimating a depth map for the dependent view, either based on already transmitted depth data or by using transmitted disparity vectors and motion parameters. The concept is applicable for multiview coding with and without depth maps. In our experiments with an extension of HEVC, average bit rate savings of about 11% for the dependent views have been measured, which result in approximately 4-5% overall bit rate savings for a 3 view configuration including depth data.
Motion vector inheritance for high efficiency 3D video plus depth coding

This paper describes a new mode for efficient encoding of depth map data that are associated with a video signal. Since the motion characteristics (i.e., block partitioning and corresponding motion vectors) of the video signal and its associated depth signal are typically similar, a motion vector inheritance (MVI) mode, where the data that are already transmitted for the video picture can be reused for efficient encoding of the depth map, has been introduced. Experimental results show averaged total bitrate reductions in terms of Bjontegaard-Delta bitrate of about 1.4% for a 2-view scenario and about 1.1% for a 3-view scenario, when averaged over all, coded and synthesized, views. This corresponds to bitrate savings for the depth signal of about 18% for the 2-view case and about 10% for the 3-view case.
Joint rate-distortion optimization of transform coefficients for spatial Scalable Video Coding using SVC

The recently finalized scalable video coding (SVC) extension of the H.264/AVC video coding standard supports encoding of video sequences at different spatial resolutions within one single scalable bit-stream. In order to achieve an improved coding efficiency compared to simulcast, SVC allows so-called "inter-layer prediction," where texture, motion, and residual data of the lower resolution layer are exploited for the encoding of the higher resolution layer. In this paper, we extend the ideas presented in our previous work by M. Winken et al (2007), and describe an approach how the dependencies caused by the inter-layer residual prediction can be utilized in the selection of the transform coefficient values for the lower resolution layer. Our experimental results show gains of 0.5 dB luma PSNR compared to our previous approach for the high resolution layer with no impact on the base layer coding efficiency.
Performance comparison of video coding standards using Lagrangian coder control

A unified approach to the coder control of video coding standards such as MPEG-2, H.263, MPEG-4, and the draft video coding standard JVT/H.26L/AVC is presented. Using this unified framework, the performance of the various standards is compared by means of PSNR and subjective testing results. The results indicate that JVT/H.26L/AVC compliant encoding can typically achieve essentially the same objective PSNR reproduction quality as encoders that are compliant with previous standards while requiring as little as 60% or less of the bit rate of the next best standard, particularly for higher-latency applications and particularly for more difficult source material. Subjective testing shows that the bit savings produced by this draft standard are even larger than the PSNR results indicate.
Comparison of the Coding Efficiency of Video Coding Standards—Including High Efficiency Video Coding (HEVC)

The compression capability of several generations of video coding standards is compared by means of peak signal-to-noise ratio (PSNR) and subjective testing results. A unified approach is applied to the analysis of designs, including H.262/MPEG-2 Video, H.263, MPEG-4 Visual, H.264/MPEG-4 Advanced Video Coding (AVC), and High Efficiency Video Coding (HEVC). The results of subjective tests for WVGA and HD sequences indicate that HEVC encoders can achieve equivalent subjective reproduction quality as encoders that conform to H.264/MPEG-4 AVC when using approximately 50% less bit rate on average. The HEVC design is shown to be especially effective for low bit rates, high-resolution video content, and low-delay communication applications. The measured subjective improvement somewhat exceeds the improvement measured by the PSNR metric.
Adaptive motion model selection using a cubic spline based estimation framework

A block based video coder that supports multiple motion models is proposed. Apart from the typical translational motion model, we employ parametric models to more accurately represent complex motions that occur in video sequences. A novel method for estimating the warping parameters in a rate-constrained way is presented. A cubic spline framework is utilized to obtain fractional-accuracy samples for motion compensation. Efficient motion vector prediction schemes are developed to maintain the continuity of the predictor in spite of different motion models. Bit rate savings up to 11.7% in IPPP and 9.3% in Hierarchical B pictures are shown compared to an improved H.264/AVC reference.
Performance Analysis of SVC

This paper provides a performance analysis of the scalable video coding (SVC) extension of H.264/AVC. A short overview presenting the main functionalities of SVC is given and main issues in encoder control and bit stream extraction are outlined. Some aspects of rate-distortion optimization in the context of SVC are discussed and strategies for derivation of optimized configurations relative to the investigated scalability scenarios are presented. Based on these methods, rate-distortion results for several SVC configurations are presented and compared to rate-distortion optimized H.264/AVC single layer coding. For reference, a comparison to rate-distortion optimized MPEG-4 visual (advanced simple profile) coding results is provided. The results show that the performance gap between single layer coding and scalable video coding can be very small and that SVC clearly outperforms previous video coding technology such as MPEG-4 ASP.
Source Coding: Part I of Fundamentals of Source and Video Coding

Digital media technologies have become an integral part of the way we create, communicate, and consume information. At the core of these technologies are source coding methods that are described in this monograph. Based on the fundamentals of information and rate distortion theory, the most relevant techniques used in source coding algorithms are described: entropy coding, quantization as well as predictive and transform coding. The emphasis is put onto algorithms that are also used in video coding, which will be explained in the other part of this two-part monograph.