nils-herrmann/clean_scirepeval huggingface dataset:
Encryption for high efficiency video coding with video adaptation capabilities

Video encryption techniques enable applications like digital rights management and video scrambling. Applying encryption on the entire video stream can be computationally costly and prevents advanced video modifications by an untrusted middlebox in the network, like splicing, quality monitoring, watermarking, and transcoding. Therefore, encryption techniques are proposed which influence a small amount of the video stream while keeping the video compliant with its compression standard, High Efficiency Video Coding. Encryption while guaranteeing standard compliance can cause degraded compression efficiency, so depending on their bitrate impact, a selection of encrypted syntax elements should be made. Each element also impacts the quality for untrusted decoders differently, so this aspect should also be considered. In this paper, multiple techniques for partial video encryption are investigated, most of them having a low impact on rate-distortion performance and having a broad range in scrambling performance.
Depth-based view synthesis using pixel-level image inpainting

Depth-based view synthesis can produce novel realistic images of a scene by view warping and image inpainting. This paper presents a depth-based view synthesis approach performing pixel-level image inpainting. The proposed approach provides great flexibility in pixel manipulation and prevents random effects in texture propagation. By analyzing the process generating image holes in view warping, we firstly classify such areas into simple holes and disocclusion areas. Based on depth information constraints and different strategies for random propagation, an approximate nearest-neighbor match based pixel-level inpainting is introduced to complete holes from the two classes. Experimental results demonstrate that the proposed view synthesis method can effectively produce smooth textures and reasonable structure propagation. The proposed depth-based pixel-level inpainting is well suitable to multi-view video and other higher dimensional view synthesis settings.
Complexity scalability in video coding based on in-band motion-compensated temporal filtering

Scalable wavelet-based video coding is of paramount importance in applications in order to adapt the video content to the channel conditions and to enable the selection of a variety of user preferences in terms of quality, resolution and frame-rate. Apart of this, a growing number of mobile devices on which video has to be decoded, stresses the need for complexity scalability to cope with their limited computational capabilities. In this context, the paper focuses on wavelet-based scalable video coding based on in-band motion-compensated temporal filtering and addresses the problem of achieving complexity scalability in the complete-to-overcomplete discrete wavelet transform (CODWT) module employed by such architectures. The proposed methods demonstrate that this can be achieved at the cost of a limited and controllable penalty in the overall coding performance.
Embedded multiple description scalar quantizers for progressive image transmission

Robust progressive image transmission over unreliable channels with variable bandwidth requires multiple description coding (MDC) systems that produce highly error-resilient embedded bitstreams. The proposed embedded multiple description scalar quantizers (EMDSQ) meet the desired features consisting of a high redundancy level, fine grain rate adaptation and progressive transmission of each description. Experimental results show that EMDSQ yield better rate-distortion performance in comparison to the multiple description uniform scalar quantizers; (MDUSQ) previously proposed in the literature. Moreover, the generalized form of EMDSQ targeting an arbitrary number of channels is proposed, which offers the possibility of designing realistic coders for practical multi-channel communication systems.
MESHGRID-a compact, multiscalable and animation-friendly surface representation

MESHGRID is a novel, compact, multiscalable and animation-friendly surface representation method, which has been introduced in MPEG-4 . The MESHGRID representation attaches a description of the "global connectivity" between the vertices on the object's surface (i.e., the 3-D connectivity wireframe) to a regular 3-D grid of points (i.e., the reference grid). MESHGRID efficiently encodes the 3-D connectivity wireframe by using a new type of 3-D extension of Freeman chain-code. MESHGRID does not explicitly store the polygons of the surface, since the 3-D connectivity wireframe has particular connectivity properties allowing for the unambiguous derivation of the triangulation. The reference grid is a smooth vector field defined on a regular discrete 3-D space. This grid is efficiently compressed by using an embedded 3-D wavelet-based multiresolution intra-band coding algorithm. MESHGRID can be efficiently exploited for QoS since it allows for three types of scalability in both view-dependent and view-independent scenarios, including: 1) resolution scalability, i.e., the adaptation of the number of transmitted vertices; 2) shape precision, i.e., the adaptive reconstruction of the reference grid positions; and 3) vertex position scalability, i.e., the change of the precision of known vertex positions with respect to the reference grid. Furthermore, in addition to the classical vertex-based animation, MESHGRID also supports specific animation capabilities, such as: 1) rippling effects by changing the position of the vertices relative to corresponding reference grid points and 2) reshaping on a hierarchical basis of the regular reference grid and its attached vertices.
Optimized wavelet-based texture representation and streaming for GPU texture mapping

Texture compression is an important tool in real time texture mapping on several levels. Besides from increasing sampling performance due to cache efficiency and lower memory requirements, it can significantly decrease texture loading times. In bandwidth constrained situations, a texture streaming system is not always able to load the required texture data in time, either stalling the visualization or forcing the use of a placeholder texture. In this paper we propose a wavelet-based texture representation and streaming system which optimizes for maximal visual quality within bandwidth and real time constraints.
Scalable Joint Source and Channel Coding of Meshes

This paper proposes a new approach for joint source and channel coding (JSCC) of meshes, simultaneously providing scalability and optimized resilience against transmission errors. An unequal error protection approach is followed, to cope with the different error-sensitivity levels characterizing the various resolution and quality layers produced by the input scalable source codec. The number of layers and the protection levels to be employed for each layer are determined by solving a joint source and channel coding problem. In this context, a novel fast algorithm for solving the optimization problem is conceived, enabling a real-time implementation of the JSCC rate-allocation. An instantiation of the proposed JSCC approach is demonstrated for MeshGrid, which is a scalable 3-D object representation method, part of MPEG-4 AFX. In this context, the L-inflnite distortion metric is employed, which is to our knowledge a unique feature in mesh coding. Numerical results show the superiority of the L-inflnite norm over the classical L-2 norm in a JSCC setting. One concludes that the proposed joint source and channel coding approach offers resilience against transmission errors, provides graceful degradation, enables a fast real-time implementation, and preserves all the scalability features and animation capabilities of the employed scalable mesh codec.
Spatial-domain unidirectional DVC with side-information dependent correlation channel estimation

Present distributed video coding (DVC) approaches assume the correlation channel to be side-information independent (SII). We have recently demonstrated that in reality the correlation channel in video is side-information dependent (SID) and that DVC systems which make SII assumptions suffer a significant performance penalty, depending entirely on the correlation statistics of the video data. In this paper, we present a novel spatial domain unidirectional DVC codec which is based on a novel SID technique enabling advanced correlation channel estimation at the decoder starting from a partial knowledge of it. Experimental results show that the proposed codec achieves superior performance compared to the state-of-the-art in Wyner-Ziv video coding while operating without a feedback channel.
Considerations regarding the influence of contact resistance on the contacts of low voltage electrical equipment

The electrical contacts are important elements which can be found on all of the electrical installations from the power source to the consumer. Also, the electrical contacts have an important role in the construction and operation of low voltage electrical equipment. The presence of an electrical contact on a current path always introduce an additional electrical resistance, named contact resistance. In this paper is studied the influence of the voltage drops to contact resistance, respectively to contact temperature of the low voltage electrical equipment.
Demo: depth estimation for 1K-pixel stereo visual sensors

This demonstrator explores the applicability of depth estimation based on stereo video with extremely low resolution, i.e., 30×30 pixels. To handle this resolution, a disparity estimation technique, composed of local correlation-based matching of two low-resolution stereo images followed by segmentation-driven post-processing, is proposed. The demonstrator includes a setup where a stereo visual sensor is connected to a laptop computer, running the proposed depth estimation method in realtime and displaying the resulting disparity maps. In addition, an interface is available to give the user control over the proposed algorithm parameters. To illustrate the superior performance, the results of proposed method can be readily compared to disparity maps generated using a typical global correlation-based depth estimation algorithm.
Complete-to-overcomplete discrete wavelet transforms: theory and applications

A new transform is proposed that derives the overcomplete discrete wavelet transform (ODWT) subbands from the critically sampled DWT subbands (complete representation). This complete-to-overcomplete DWT (CODWT) has certain advantages in comparison to the conventional approach that performs the inverse DWT to reconstruct the input signal, followed by the a/spl grave/-trous or the lowband shift algorithm. Specifically, the computation of the input signal is not required. As a result, the minimum number of downsampling operations is performed and the use of upsampling is avoided. The proposed CODWT computes the ODWT subbands by using a set of prediction-filter matrices and filtering-and-downsampling operators applied to the DWT. This formulation demonstrates a clear separation between the single-rate and multirate components of the transform. This can be especially significant when the CODWT is used in resource-constrained environments, such as resolution-scalable image and video codecs. To illustrate the applicability of the proposed transform in these emerging applications, a new scheme for the transform-calculation is proposed, and existing coding techniques that benefit from its usage are surveyed. The analysis of the proposed CODWT in terms of arithmetic complexity and delay reveals significant gains as compared with the conventional approach.
A comparative study of the winding type influence on the noise level of two-speed three-phase induction motors

The goal of this work is to present the study of the influence of the winding - double layer or single layer - to the global noise level of an induction motor. For this purpose, two variable speed induction motors have been studied, of the type M3AA 71 B2/4 manufactured by Electroprecizia S.A. Săcele, Romania, with Dahlander windings, star connected - for the low speed and double star connected - for the high speed. The motors are modelled from magnetic and mechanical point of view with finite element softwares. The noise-to-frequency characteristics have been determined by investigations in a semi-anechoic chamber.
Perceptual video quality assessment in HTTP adaptive streaming

In this paper, we propose a quality metric for video transmitted over HTTP adaptive streaming (HAS). Perceived video quality in HAS strongly depends on the employed rate adaptation mechanisms, transmission conditions and buffer filling levels. Predicting perceived quality in HAS is an open problem, due to the lack of appropriateness of existing metrics. To overcome this problem, a quality metric based on extensive user evaluations is proposed in this paper. A thorough investigation is carried out, accounting for all possible types of video quality impairments occurring in HAS applications. The proposed metric correlates well with the perceived quality, allowing for optimizing the HAS descriptions and of the switching mechanism between them. It is also shown that the classical intrinsic quality metrics (PSNR, SSIM, VQM) fail to predict user-perceived video quality due to quality fluctuations inherent to HAS systems.
Intra-frame video coding using an open-loop predictive coding approach

A novel coding approach, applying open-loop coding principles in predictive coding systems is proposed in this paper. The proposed approach is instantiated with an intra-frame video codec employing the transform and spatial prediction modes from H.264. Additionally, a novel rate-distortion model for open-loop predictive coding is proposed and experimentally validated. Optimally allocating rate based on the proposed model provides significant gains in comparison to a straightforward rate allocation not accounting for drift. Furthermore, the proposed open-loop predictive codec provides gains of up to 2.3 dB in comparison to an equivalent closed-loop intra-frame video codec employing the transform, prediction modes and rate-allocation from H.264. This indicates that, with appropriate drift compensation, open-loop predictive coding offers the possibility for further improving the compression performance in predictive coding systems.
Performances optimization and characteristics of the voltage generated by multilevel inverters

Several fixed frequency applications of multilevel converters require a very low level of distortion factor of the output voltage. Bringing the output voltage to a form as close as possible to a sine wave is usually done through linearization methods of the Newton-Raphson algebraic equations. The method proposed in section III uses for the waveforms optimization a genetic algorithm, having a positive impact on the total harmonic distortion reduction. Experimental validation of the method is performed using a programmable source which drives an induction motor.
Robust stereo matching using census cost, discontinuity-preserving disparity computation and view-consistent refinement

Stereo matching has been one of the most active research topics in computer vision domain for many years resulting in a large number of techniques proposed in the literature. Nevertheless, improper combinations of available tools cannot fully utilize the advantages of each method and may even lower the performance of the stereo matching system. Moreover, state-of-the-art techniques are usually optimized to perform well on a certain input dataset. In this paper we propose a framework to combine existing tools into a stereo matching pipeline and three different architectures combining existing processing steps to build stereo matching systems which are not only accurate but also efficient and robust under different operating conditions. Thorough experiments on three well-known datasets confirm the effectiveness of our proposed systems on any input data.
Distributed coding of endoscopic video

Triggered by the challenging prerequisites of wireless capsule endoscopic video technology, this paper presents a novel distributed video coding (DVC) scheme, which employs an original hash-based side-information creation method at the decoder. In contrast to existing DVC schemes, the proposed codec generates high quality side-information at the decoder, even under the strenuous motion conditions encountered in endoscopic video. Performance evaluation using broad endoscopic video material shows that the proposed approach brings notable and consistent compression gains over various state-of-the-art video codecs at the additional benefit of vastly reduced encoding complexity.
Efficient MRF-based disocclusion inpainting in multiview video

View synthesis using depth image-based rendering generates virtual viewpoints of a 3D scene based on texture and depth information from a set of available cameras. One of the core components in view synthesis is image inpainting which performs the reconstruction of areas that were occluded in the available cameras but are visible from the virtual viewpoint. Inpainting methods based on Markov random fields (MRFs) have been shown to be very effective in inpainting large areas in images. In this paper, we propose a novel MRF-based in-painting method for multiview video. The proposed method steers the MRF optimization towards completion from background to foreground and exploits the available depth information in order to avoid bleeding artifacts. The proposed approach allows for efficiently filling-in large disocclusion areas and greatly accelerates execution compared to traditional MRF-based inpainting techniques. The experimental results show that view synthesis based on the proposed inpainting method systematically improves performance over the state-of-the-art in multiview view synthesis. Average PSNR gains up to 1.88 dB compared to the MPEG View Synthesis Reference software were observed.
The No-Rate-Loss Property of Wyner-Ziv Coding in the Z-Channel Correlation Case

In this letter, we present the exact Wyner-Ziv limit for binary source coding with side information correlated by a Z-channel and with the Hamming-distance as distortion metric. A surprising discovery is that, unlike the general case, Wyner-Ziv coding under this setup does not suffer a rate loss compared to source coding with side information available at both the encoder and the decoder. Highlighting the significance of our finding, we note that this is an additional case for which Wyner-Ziv coding is shown not to suffer a rate loss apart from the quadratic Gaussian case, proven by Wyner and Ziv, and its generalization by Pradhan et al.
Single-tooth winding induction motor with external rotor for electric vehicle applications

Design aspects and FEM simulation results of a six-phase induction motor consisting of two three-phase single tooth concentrated windings with a 30° shift between, and an external rotor are presented in this paper. The main goal is to find a suitable candidate for electric vehicle applications which require simplified manufacturing process, reduced fabrication costs, and achieving high efficiencies at fractional loads at the same time.
Canonic signed digit Chebyshev FIR filter design

A new algorithm is presented for the design of fixed point finite impulse response (FIR) digital filters that can be realized using a minimal number of adders while satisfying both the desired hardware implementation constraints and the frequency domain design constraints. The proposed algorithm makes use of a two-stage search method with a new soft-switching optimization criterion, minimizing the Chebyshev error norm in a discrete canonic signed digit (CSD) space. The proposed design method is implemented as a Matlab-based software package (CSDFIR) that allows the design of both Chebyshev optimal floating point and fixed point CSD FIR filters.
Coding of digital imagery for transmission over multiple noisy channels

This paper presents a multiple description image coding scheme that facilitates the transmission of digital imagery over multiple noisy channels. The proposed scheme divides the image into smaller parts that are transmitted over the individual channels of an inverse multiplexing system. The division or splitting is done in such a fashion that it facilitates the interpolation of lost coefficients in the case of one or more channel failures. At the receiver, the image is reconstructed by proper assembly of the data received from each channel. In case of channel failure, the missing coefficients are estimated from the available data with the use of a novel post-processing scheme. For operation over four noisy channels with various bit error probabilities, we investigate the quantitative and subjective performance of the proposed system for the case of multiple channel failures.
Visual Saliency Prediction Using a Mixture of Deep Neural Networks

Visual saliency models have recently begun to incorporate deep learning to achieve predictive capacity much greater than previous unsupervised methods. However, most existing models predict saliency without explicit knowledge of global scene semantic information. We propose a model (MxSalNet) that incorporates global scene semantic information in addition to local information gathered by a convolutional neural network. Our model is formulated as a mixture of experts. Each expert network is trained to predict saliency for a set of closely related images. The final saliency map is computed as a weighted mixture of the expert networks’ output, with weights determined by a separate gating network. This gating network is guided by global scene information to predict weights. The expert networks and the gating network are trained simultaneously in an end-to-end manner. We show that our mixture formulation leads to improvement in performance over an otherwise identical non-mixture model that does not incorporate global scene information. Additionally, we show that our model achieves better performance than several other visual saliency models.
JPEG2000-based shape adaptive algorithm for the efficient coding of multiple regions-of-interest

The JPEG2000 standard supports two methods to code regions-of-interest (ROIs) in an image-the maxshift method and the scaling-based method. Compared to the maxshift method, the scaling-based method is preferable in many applications because it allows the nonROI (background) region to be partially coded prior to coding all of the ROIs. This is accomplished by supporting arbitrary bitplane shift factors and by filling the most significant bit-planes of the nonROI region with zeros after the ROI bitplanes have been shifted up in value. In both of these methods, the embedded block coding with optimum truncation (EBCOT) algorithm is then applied to code the wavelet coefficients. However, when multiple regions-of-interest need to be coded, the performance of the scaling-based method degrades significantly since the EBCOT coder is no longer able to efficiently code the nonROI region, which is now less contiguous as compared to the single-ROI case. Also, the large header information that is required in JPEG2000 for each ROI degrades the coding performance. This paper presents an improved scaling-based method for the efficient coding of multiple, arbitrarily-shaped ROIs using a modified EBCOT algorithm. The proposed method utilizes the shape information of the different ROIs to generate a stripe mask, which is then used to optimize the coding performance. Coding results and comparisons with the JPEG2000 scaling-based method are presented to illustrate the improved performance of the proposed scheme.