nils-herrmann/clean_scirepeval huggingface dataset:
DSP implementation of digital image stabilizer

A digital image stabilization system compensates the image movement caused by hand jiggle for the image sequence captured by a hand-held video camera. In this paper, a simplified stabilization algorithm based on our previous work is presented. The algorithm performs block-based motion estimation on 16 local 16/spl times/16 blocks and uses a median filter to estimate the global motion. It reduces the complexity by confining the motion estimation to a small number of blocks of the image. This greatly facilitates the implementation of the algorithm on BF561, a DSP processor of analog device. Details of the DSP implementation are described.
Directing visual attention by subliminal cues

Unconscious attention shift has been proven to be automatic, effortless, and unresisting; however, whether it is applicable to images of complex scene remains to be verified. We propose a novel method for directing human visual attention by flashing a short-duration visual stimulus before presenting the image. This method directs viewer's visual attention to an arbitrary location in the image without engaging the viewer's awareness. Unlike previous studies using simple stimuli (e.g. simple geometric figures, image of uniform color, or artificial white-noise), we use complex color images for guiding unconscious visual attention in real-world. To our best knowledge, this is the first study demonstrating that short-duration cues presented at arbitrary locations can attract human visual attention in a complex scene. The proposed method is useful for applications that require efficient and unresisting attention shift to the target image area.
Using Motion from Orthographic Views to Verify 3-D Point Matches

The specific problem addressed by the authors is how to detect the true match of a fourth point from among candidate matches in a situation in which three points have already been matched. The two sets of points to be matched are both subject to measurement errors. The depth error is more dominant than errors in the other two coordinates; however, the exact statistical distribution of the measurement errors is not known. The authors present a new method for solving the problem. The method is based on the technique of motion analysis using orthographic views. It discards the noisy z (depth) coordinates and uses only the x and y coordinates of the points to verify the match. The effect of depth errors on the motion estimate is completely prevented. Results show that this method is substantially more effective than previous methods that use all three coordinates.
Perceptully lossless video re-encoding for cloud transcoding

In this paper, we present a perceptually lossless video re-encoding approach to cloud transcoding based on a just noticeable distortion (JND) model. The bitrate is minimized by adaptive step size and dynamic rounding offset adjustment. On the average, the proposed approach achieves 9.7% overall bitrate reduction compared to the H.264/AVC JM reference encoder under the same coding condition. The performance of the resulting cloud transcoding is further verified by a subjective test.
A complexity-aware live streaming system with bit rate adjustment

For a live streaming server, it is highly desirable to allocate the available computational resource and bandwidth to each channel fairly and efficiently. In this paper, we propose a complexity-aware live streaming system with bit rate adjustment that can handle the allocation of bandwidth and computational resource of a live streaming server. The proposed system encodes the input videos at different quality levels based on the priority of the input videos and the available computational resource. It incorporates a bit rate adjustment mechanism to compensate for the video quality drop resulted from the quality level change of high priority encoders. The resulting system is able to handle channels more efficiently because the complexity of high priority encoders can also be dynamically adjusted with little quality drop. A new complexity adjustment method is developed that enables the system to stabilize more quickly and minimizes the variance of the time buffer. The experimental results show that the system can handle more channels while still maintaining the quality of high priority encoders. The proposed system is applicable to multimedia home gateways, surveillance, IP-based TV, and on-line sports game relays.
Emotional Accompaniment Generation System Based on Harmonic Progression

A music piece consists of melody and accompaniment in many genres. In this paper, we present a system to automatically generate accompaniment that evokes specific emotions for a given melody. In particular, we propose harmonic progression and onset rate as two key features for emotion-based accompaniment generation. The former refers to the progression of chords, and the latter refers to the number of music events (such as notes and drums) in a unit time. The harmonic progression and the onset rate are altered according to the specified emotion represented by the valence and arousal parameters, respectively. The performance of the system is evaluated subjectively, and the result shows a perfect positive Spearman correlation between the specified emotion and the perceived emotion.
Feature-Based Full-Frame Image Stabilization

Digital image stabilization usually discards boundary pixels and outputs a smaller video. In this paper, we present a new digital image stabilization algorithm that preserves the frame size of output video by pixel filling. The proposed algorithm eliminates the accumulation error by directly estimating the global motions in a transformation chain with reference to a fixed frame. A feature matching method is adopted to save the computational cost of the global motion estimation and to handle large motions. The experimental results show that the proposed algorithm produces stabilized full-frame video sequences with better frame alignment.
Radiometric Compensation of Images Projected on Non-White Surfaces by Exploiting Chromatic Adaptation and Perceptual Anchoring

Flat surfaces in our living environment to be used as replacements of a projection screen are not necessarily white. We propose a perceptual radiometric compensation method to counteract the effect of color projection surfaces on image appearance. It reduces color clipping while preserving the hue and brightness of images based on the anchoring property of human visual system. In addition, it considers the effect of chromatic adaptation on perceptual image quality and fixes the color distortion caused by non-white projection surfaces by properly shifting the color of the image pixels toward the complementary color of the projection surface. User ratings show that our method outperforms the existing methods in 974 out of 1020 subjective tests.
Automatic chord recognition for music classification and retrieval

As one of the most important mid-level features of music, chord contains rich information of harmonic structure that is useful for music information retrieval. In this paper, we present a chord recognition system based on the N-gram model. The system is time-efficient, and its accuracy is comparable to existing systems. We further propose a new method to construct chord features for music emotion classification and evaluate its performance on commercial song recordings. Experimental results demonstrate the advantage of using chord features for music classification and retrieval.
Analysis of the effect of calibration error on light field super-resolution rendering

Light field photography, which has recently drawn considerable attention, provides novel functionalities such as refocusing and depth estimation at the same time. However, the resolution of the rendered refocus image is incomparably lower than the number of light ray samples in the light field. In this paper, we show that super-resolution can be performed to bridge the gap and that deconvolution, which is missing in most previous methods, is essential to the success of light field super-resolution rendering. In addition, we investigate the effect of four different kinds of camera calibration error on the quality of rendered images. Given an expected level of image quality, the upperbound of the camera calibration error is analyzed.
JND-based enhancedment of perceptibility for dim images

Maintaining image quality under various lighting conditions is critical to portable multimedia devices. In this paper, an image enhancement algorithm is proposed to deal with extremely dim LCD backlight (or strong ambient light) under which the image often becomes imperceptible. The crux of our idea is to keep the detail content of the image in the visible luminance range. To do that, a two-layer image decomposition architecture based on the just noticeable difference (JND) theory is proposed for extracting the details, and a boosting scheme is applied to the details that are in the low intensity regions of the image. Experimental results are provided to show the superiority of the proposed algorithm.
Focus Profile Modeling

A focus profile depicts the image sharpness (or focus value) as the lens sweeps along the optical axis of a camera. Accurate modeling of the focus profile is important to many imaging tasks. In this paper, we present an approach to focus profile modeling that makes the search of in-focus lens position a mathematically tractable problem, and hereby improves the efficiency and accuracy of image acquisition. The proposed approach entails a transformation that converts the representation of a focus profile to quadratic form. An important feature of the approach is that no prior knowledge of the focus measurement technique is required. Experimental results are provided to demonstrate the effectiveness of the approach.
Fast Decision of Block Size, Prediction Mode, and Intra Block for H.264 Intra Prediction

The spatial-domain intra prediction scheme of H.264 has high computational complexity, especially for the High Profile as it incorporates the additional intra 8 × 8 prediction mode. To address this issue, we explore the hierarchy of H.264 mode decision process in this paper and adopt an approach that is in synchrony with the mode decision hierarchy. In particular, we propose a variance-based algorithm for block size decision, an improved filter-based algorithm for prediction mode decision using contextual information, and a selection algorithm for intra block decision that exploits the relation between the rate-distortion characteristic and the best coding type. Performance comparison is provided to show the improvement of the proposed algorithms over previous methods.
Rounding Mismatch Between Spatial-Domain and Transform-Domain Video Codecs

The mismatch between a spatial-domain encoder and a transform-domain decoder due to rounding can cause serious video quality degradation after a series of inter-coded frames. The mismatch is rooted on the fact that rounding is a nonlinear operation, and hence its equivalent in the transform domain does not exist. We analyze the mathematical property of the rounding operation and propose a practical solution that provides an optimal approximation of the rounding operation in the transform-domain. The proposed solution is able to reduce the mismatch and preserve image quality. Experimental results are shown to demonstrate the effectiveness of the solution
Image Quality Enhancement for Low Backlight TFT-LCD Displays

Reducing LCD backlight saves power consumption of a portable device, but it also decreases the contrast and brightness of the displayed image. Previous approaches adjust the backlight level frame by frame to reach a specified image quality level without optimizing the image quality. In contrast, the proposed method adjusts the backlight to meet the target power level while maintaining the image quality. This is achieved by performing brightness compensation and local contrast enhancement in accordance with the given backlight level. Experimental results show that the proposed algorithm outperforms previous methods.
Fusion of visual attention cues by machine learning

A new computational scheme for visual attention modeling is proposed. It adopts both low-level and high-level features to predict visual attention from a video signal and fuses the features by using machine learning. We show that such a scheme is more robust than those using purely single level features. Unlike conventional techniques, our scheme is able to avoid perceptual mismatch between the estimated saliency and the actual human fixation. We show that selecting the representative training samples according to the fixation distribution improves the efficacy of regressive training. Experimental results are shown to demonstrate the advantages of the proposed scheme.
Light Field Acquisition using Programmable Aperture Camera

We propose a new device, programmable aperture camera (PAC), to capture 4D light field in a camera. PAC can adjust the shape of the aperture in each exposure. This allows us to capture the angular information of the light field, which is lost in regular photography. Although multiple exposures are needed to obtain a light field, the total exposure time remains the same as that of taking a single regular photograph at the same image quality level. As opposed to previous techniques that seriously reduce the spatial resolution, PAC captures the image at full spatial resolution and allows adjustable angular resolution. Also its manufacturing cost is much lower than previous techniques. We describe the PAC prototype and demonstrate how digital refocusing is made possible by using the captured light field.
H.264/AVC-Based Multiple Description Coding Scheme

A new multiple description coding (MDC) scheme is proposed in this paper. It utilizes the advanced video coding tools and features provided in H.264/AVC to introduce redundancy into descriptions. The proposed MDC scheme produces two descriptions, each consisting of two slice groups. One of them, called main slice group (MSG), is encoded in the normal way as main information. The other one, called side slice group (SSG), is encoded with fewer bits as redundancy by using larger quantization step sizes. Spatial and temporal correlations between neighboring macroblocks in video frames are exploited to achieve efficient redundancy coding. Experimental results show that the proposed MDC scheme achieves better rate-distortion (R-D) performance than previous slice-group based MDC schemes.
Bandwidth Estimation of in-Home Power Line Networks

Bandwidth information is critical to robust real-time multimedia transmission. However, existing bandwidth estimation (BWE) methods developed for the Internet or wireless networks are inadequate for power line networks due to the difference in media access control scheduling policies and channel noise characteristics. In this paper, we investigate the characteristics of in-home power line networks and present a real-time BWE scheme. By varying the packet size at a given physical-layer line rate, we find that the transmission rate has a cutoff point at which the data traffic starts to suffer from packet loss and that the cutoff rate is approximately proportional to the packet size. Moreover, as the transmission rate becomes greater than the cutoff point, the packet loss rate increases. Based on the evaluation of in-home power line networks, we propose a BWE scheme that estimates the cutoff rate from physical-layer line rate, data transmission rate, packet size, and packet loss rate. This scheme applies an iterative packet probing algorithm to estimate the available bandwidth. Experimental results show that the proposed scheme achieves good estimation accuracy.
Constant-Quality Rate Control Algorithm for Multiple Encoders with Single Video Source

In this paper, we develop a constant-quality rate control algorithm for a surveillance system that consists of one "base encoder" for encoding a down-sampled full-view version of the input video sequence and one "region of interest (ROI) encoder" for encoding the region of interest of the input video at the original resolution. Exploiting the inter-relationship between these two independent encoders, the bits for the ROI encoder are allocated according to the distortion obtained from the base encoder. Simulation results show that the proposed algorithm significantly reduces the image quality variation. The overall quality is improved and the bit-rate is saved as compared to the rate control algorithm in JM 8.4
Improving the coding of regions of interest

This paper considers a video coding system for surveillance applications. It consists of one "base encoder" that encodes a down-sampled, full-view version of the input video sequence and one "region of interest" (ROI) encoder that encodes an ROI of the video sequence at the original image resolution. An important requirement of the video coding system is that the ROI bit stream and the base bit stream should be independently decodable. We explore the inter-relationship between the full-view video sequence and the ROI video sequence and apply it to improve the computational efficiency of the ROI encoder. The proposed algorithm achieves an average of 170% speedup
Realism assessment of color compatibility using a single image

In this paper, we present a study of the realism of color image composites. Assessing the realism of image composites has emerged as a new field of image processing due to the advances in digital imaging and communications. However, when making image composites, users often suffer from color incompatibility between the inserted object and the background. We observe two properties that help make an image composite look realistic. The first property is related to the color similarity between different segments of the image, and the second one is related to the consistency of color deviation between the segments. These two properties only require information available from a single image. An algorithm based on these two properties is proposed for assessment of image realism. Effectiveness of the algorithm is demonstrated.
Enhancement of phase detection for autofocus

Phase detection autofocus (PDAF) is a technique that uses sensors on left and right pixels to determine the relative position between the object and the focal plane. When an image is out of focus, a shift between the assembled left and right pixels is resulted, which can be used to determine the lens movement during the autofocus process. However, the presence of noise and blur often affects the accuracy of shift estimation and hence the performance of autofocus. In this paper, we propose a method to enhance phase detection for such sensors. A Gaussian filter is applied to overcome the adverse effect of image noise and blur. Experiments are conducted to show that the proposed method leads to a more accurate estimate of lens movement than the traditional phase correlation.
Vector representation of emotion flow for popular music

The flow of emotion expressed by music through time is a useful feature for music information indexing and retrieval. In this paper, we propose a novel vector representation of emotion flow for popular music. It exploits the repetitive verse-chorus structure of popular music and connects a verse (represented by a point) and its corresponding chorus (another point) in the valence-arousal emotion plane. The proposed vector representation visually gives users a snapshot of the emotion flow of a popular song in an intuitive and instant manner, more effective than the point and curve representations of music emotion flow. Because many other genres also have repetitive music structure, the vector representation has a wide range of applications.
Component Tying for Mixture Model Adaptation in Personalization of Music Emotion Recognition

Personalizing a music emotion recognition model is needed because the perception of music emotion is highly subjective, but it is a time-consuming process. In this paper, we consider how to expedite the personalization process that begins with a general model trained offline using a general user base and progressively adapts the model to a music listener using the emotion annotations of the listener. Specifically, we focus on reducing the number of user annotations needed for the personalization. We investigate and evaluate four component tying methods: single group tying, quadrantwise tying, hierarchical tying, and random tying. These methods aim to exploit the available annotations by identifying related model parameters on-the-fly and updating them jointly. In the evaluation, we use the AMG1608 dataset, which contains the clip-level valence-arousal emotion ratings of 1608 30-s music clips annotated by 665 listeners. Also, we use the acoustic emotion Gaussians model as the general model that uses a mixture of Gaussian components to learn the mapping between the acoustic feature space and the emotion space. The results show that the model adaptation with component tying requires only 10–20 personal annotations to obtain the same level of prediction accuracy as the baseline model adaptation method that uses 50 personal annotations without component tying.
An investigation of single- and multi-finger nMOSFETs for the output pin ESD protection in integrated circuits

This work is referring to the nMOSFET singer-finger, multi-finger structures under the Electro-Static Discharge (ESD) zapping, and to evaluate the current distribution situations. By using the TCAD and HSpice, because of the internal parasitic resistance differences in each one finger, which can cause non-uniform turned on. Meanwhile, with different interior parasitic capacitor on each nMOSFET type, which will be inflected the device high-current-injection behavior.
Effective autofocus decision using reciprocal focus profile

In this paper, we propose a new autofocus approach that transforms the focus profile to the reciprocal domain. A key feature of this approach is that it makes the autofocus process mathematically tractable in both in-focus and out-of-focus regions, thereby allowing a digital camera or camcorder to expedite the search of the best lens position for capturing the image that has the maximum focus value. Experimental results are provided to illustrate the advantage of the proposed approach.
JPEG-2000: a new still image compression standard

This paper describes the status and directions of the emerging ISO/IEC JPEG-2000 image compression coding standard. This new work item of the Joint Photographic Expert Group (JPEG) 2000 is intended to create a unified coding standard for different types of still images (bilevel, gray-level, color) with different characteristics (natural, medical, remote sensing, text). The paper presents an overview of the various aspects of JPEG-2000 and highlights new functionalities supported by this emerging standard and its potential applications. Experimental results are shown to illustrate its performance.
Performance analysis of reconstruction-based super-resolution for camera arrays

In this paper, we look into the possibility of combining multiple images captured by a camera array into a high-resolution image by reconstruction-based super-resolution. Specifically, we analyze the effect of camera array parameters, including the number of cameras, pixel size, and sampling interval, on the quality of the super-resolved image. Our experimental results show that the pixel size of the cameras is critical to the success of resolution enhancement and that only limited resolution gain is achievable if the pixel of the cameras is not sufficiently small. Our analysis serves as a guide to the design of high-resolution camera arrays.