nils-herrmann/clean_scirepeval huggingface dataset:
Visibility-based beam tracing for soundfield rendering

In this paper we present a visibility-based beam tracing solution for the simulation of the acoustics of environment that makes use of a projective geometry representation. More specifically, projective geometry turns out to be useful for the pre-computation of the visibility among all the reflectors in the environment. The simulation engine has a straightforward application in the rendering of the acoustics of virtual environments using loudspeaker arrays. More specifically, the acoustic wavefield is conceived as a superposition of acoustic beams, whose parameters (i.e. origin, orientation and aperture) are computed using the fast beam tracing methodology presented here. This information is processed by the rendering engine to compute spatial filters to be applied to the loudspeakers within the array. Simulative results show that an accurate simulation of the acoustic wavefield can be obtained using this approach.
Clustering of human actions using invariant body shape descriptor and dynamic time warping

We propose a human action clustering method based on a 3D representation of the body in terms of volumetric coordinates. Features representing body postures are extracted directly from 3D data, making the system inherently insensitive to viewpoint dependence, motion ambiguities and self-occlusions. An invariant shape descriptor of human body is obtained in order to capture only posture-dependent characteristics, despite possible differences in translation, orientation, scale and body size. Frame-by-frame descriptions, generated from a gesture sequence, are collected together in matrices. Clustering of action matrices is eventually performed, and through a dynamic time warping (while computing the distance metric), we gain independence from possible temporal nonlinear distortions among different instances of the same gesture.
A Proposal to Suppress the Training Stage in a Coset-Based Distributed Video Codec

Distributed video coding (DVC) is a coding paradigm that gives the decoder the task to exploit the source statistics to achieve efficient compression. Many approaches to the DVC problem have recently appeared in the literature, including the PRISM codec. Instead of encoding the deterministic quantized prediction error residual, PRISM partitions the quantization lattice into cosets and sends the index of the coset each quantized coefficient belongs to. Estimating the number of cosets is of crucial importance to achieve good coding efficiency. In PRISM, this is determined during an offline training phase. The present work aims at being a starting point for the suppression of the training stage of PRISM at the cost of sending the number of cosets for each DCT coefficient. The statistics of the number of cosets are analyzed to figure out the maximum compression efficiency achievable by entropy coding. Furthermore the paper discusses some techniques that might be used to lower the amount of transmitted bits. Based on these results, directions for future works are proposed
Video phylogeny tree reconstruction using aging measures

The increasing diffusion of user-friendly editing software and online media sharing platforms has brought forth a growing on-line availability of near-duplicate (ND) videos. The need of authenticating these contents and tracing back their history has led to the investigation of forensic algorithms for the reconstruction of the video phylogeny tree (VPT), i.e., an acyclic directed graph summarizing video genealogical relationships. Unfortunately, state-of-the-art solutions for VPT reconstruction suffer from strong computational requirements. In this paper, we propose a processing age measure based on video DCT coefficients and motion vectors statistics, which enables to provide preliminary information about possible video parent-child relationship. The use of processing age allows a forensic analyst to blindly select a smaller amount of significant video pairs to be compared for VPT reconstruction. This solution grants computational complexity reduction to the overall VPT reconstruction pipeline.
Revealing the Traces of JPEG Compression Anti-Forensics

Due to the lossy nature of transform coding, JPEG introduces characteristic traces in the compressed images. A forensic analyst might reveal these traces by analyzing the histogram of discrete cosine transform (DCT) coefficients and exploit them to identify local tampering, copy-move forgery, etc. At the same time, it has been recently shown that a knowledgeable adversary can possibly conceal the traces of JPEG compression, by adding a dithering noise signal in the DCT domain, in order to restore the histogram of the original image. In this paper, we study the processing chain that arises in the case of JPEG compression anti-forensics. We take the perspective of the forensic analyst, and we show how it is possible to counter the aforementioned anti-forensic method revealing the traces of JPEG compression, regardless of the quantization matrix being used. Tests on a large image dataset demonstrated that the proposed detector was able to achieve an average accuracy equal to 93%, rising above 99% when excluding the case of nearly lossless JPEG compression.
Motion Estimation by Quadtree Pruning and Merging

In this paper we propose a rate-distortion optimized motion estimation algorithm that is built upon a quadtree structure. Each node of the quadtree represents a block in the current frame together with its motion vector, and the block size decreases from the root to the leaves. In the first step, the quadtree is pruned according to a rate-distortion criterion in order to obtain blocks of variable sizes. A further rate rebate can be achieved by merging those leaf nodes of the quadtree that can be efficiently represented by the same motion vector. The proposed merging scheme provides a reduction of up to 50% of the rate spent for the motion model with respect to the case that performs pruning only
Forward error protection for robust video streaming based on distributed video coding principles

This paper proposes an error resilient coding scheme that employs distributed video coding tools. A bitstream, produced by any standard motion-compensated predictive codec (MPEG-x, H.26x), is sent over an error-prone channel. In addition, a Wyner-Ziv encoded auxiliary bitstream is sent as redundant information to serve as a forward error correction code. At the decoder side, error concealed reconstructed frames are used as side information by the Wyner-Ziv decoder, and the corrected frame is used as a reference by future frames, thus reducing drift. We explicitly target the problem of rate allocation at the encoder side, by estimating the channel induced distortion in the transform domain. Experimental results conducted over a simulated error-prone channel reveal that the proposed scheme has comparable or better performance than a scheme where forward error correction codes are used. Moreover the proposed solution shows good performance when compared to a scheme that uses the intra-macroblock refresh procedure.
Phylogenetic analysis of near-duplicate images using processing age metrics

Recent researches on image forensics have led to the design of algorithms to study the phylogenetic relationship between near-duplicate (ND) images. The proposed solutions aim at reconstructing the image phylogeny tree (IPT), and they have immediate applications in security, law and copyright enforcement, and news tracking services. Anyway, the effectiveness of such strategies strictly depends on the accuracy in characterizing image similarities. In this paper, we show that it is possible to take into account additional information to better reconstruct the IPT. More specifically, we propose a set of features that blindly model the processing age of an image, i.e., how much an image has been edited in its lifetime. By exploiting these features, it is possible to improve the performance of IPT reconstruction by increasing the accuracy and reducing the computational complexity.
A methodology for estimating the radiation pattern of a violin during the performance

We propose a method for the estimation of the three-dimensional radiation pattern of violins, during the performance of a musician. A microphone array captures the energy radiated by the violin in different directions using beamforming based on sub-arrays. The 3D radiation pattern is estimated allowing the musician to freely move. In particular, a tracking system estimates the position and orientation of the violin. The adopted system can be also used in a mildly reverberant environment, thus allowing the musician to play in a natural fashion. The experimental results prove the accuracy and the effectiveness of the method.
Correction method for nonideal iris recognition

The use of iris as biometric trait has emerged as one of the most preferred method because of its uniqueness, lifetime stability and regular shape. Moreover it shows public acceptance and new user-friendly capture devices are developed and used in a broadened range of applications. Currently, iris recognition systems work well with frontal iris images from cooperative users. Nonideal iris images are still a challenge for iris recognition and can significantly affect the accuracy of iris recognition systems. In this paper, we propose a method to correct off-angle iris image. Taking into account the eye morphology and the reflectance properties of the external transparent layers, we can evaluate the distorting effect that is present in the acquired image. The correction algorithm proposed includes a first modeling phase of the human eye, a segmentation of the acquired image, and a simulation phase where the acquisition geometry is reproduced and the distortions are evaluated. Finally we obtain an image which does not contain the distorting effects due to jumps in the refractive index. We show how this correction process reduce the intra-class variations for off-angle iris images.
The cost of JPEG compression anti-forensics

The statistical footprint left by JPEG compression can be a valuable source of information for the forensic analyst. Recently, it has been shown that a suitable anti-forensic method can be used to destroy these traces, by properly adding a noise-like signal to the quantized DCT coefficients. In this paper we analyze the cost of this technique in terms of introduced distortion and loss of image quality. We characterize the dependency of the distortion on the image statistics in the DCT domain and on the quantization step used in JPEG compression. We also evaluate the loss of quality as measured by means of a perceptual metric, showing that a perceptually-optimized version of the anti-forensic method fails to completely conceal the forgery. Our conclusion is that removing the traces of the JPEG compression history could be much more challenging than it might appear, as anti-forensic methods are bound to leave characteristic traces.
From direction of arrival estimates to localization of planar reflectors in a two dimensional geometry

In this paper we propose a novel technique to localize planar obstacles through the measurement of the Direction of Arrival by a microphone array. The measurement of the Direction of Arrival of the reflected path is turned into a quadratic constraint where the unknowns are the line parameters of the reflector. A cost function that combines multiple constraints is then derived. A parametric description of the obstacle is found by minimization of the cost function. Some simulations and experimental results show the feasibility of the proposed method.
Subjective assessment of H.264/AVC video sequences transmitted over a noisy channel

In this paper we describe a database containing subjective assessment scores relative to 78 video streams encoded with H.264/AVC and corrupted by simulating the transmission over error-prone network. The data has been collected from 40 subjects at the premises of two academic institutions. Our goal is to provide a balanced and comprehensive database to enable reproducible research results in the field of video quality assessment. In order to support research works on Full-Reference, Reduced-Reference and No-Reference video quality assessment algorithms, both the uncompressed files and the H.264/AVC bitstreams of each video sequence have been made publicly available for the research community, together with the subjective results of the performed evaluations.
Inference of Room Geometry From Acoustic Impulse Responses

Acoustic scene reconstruction is a process that aims to infer characteristics of the environment from acoustic measurements. We investigate the problem of locating planar reflectors in rooms, such as walls and furniture, from signals obtained using distributed microphones. Specifically, localization of multiple two- dimensional (2-D) reflectors is achieved by estimation of the time of arrival (TOA) of reflected signals by analysis of acoustic impulse responses (AIRs). The estimated TOAs are converted into elliptical constraints about the location of the line reflector, which is then localized by combining multiple constraints. When multiple walls are present in the acoustic scene, an ambiguity problem arises, which we show can be addressed using the Hough transform. Additionally, the Hough transform significantly improves the robustness of the estimation for noisy measurements. The proposed approach is evaluated using simulated rooms under a variety of different controlled conditions where the floor and ceiling are perfectly absorbing.  AIRs measured in a real environment are also given. Additionally, results showing the robustness to additive noise in the TOA information are presented, with particular reference to the improvement achieved through the use of the Hough transform.
No-reference modeling of the channel induced distortion at the decoder for H.264/AVC video coding

This paper proposes a model for estimating, at the decoder side, the distortion induced by the transmission over an error-prone channel, when error-free reconstructed frames are not available as a reference. The proposed estimation model considers explicitly the temporal error concealment algorithm adopted at the decoder. In the evaluation of the induced distortion, we model the effects of the absence of motion vectors and prediction residuals in the decoding process. In addition, we take into account the error propagation along successive frames. Experimental results conducted over real video sequences coded with the state-of-art H.264/AVC video coding standard validate the proposed model. In fact, the distortion estimated when no reference is available is strongly correlated both at the frame and group of pictures level with the actual distortion. This technique represents an effective no-reference video quality monitoring tool that can be embedded in any H.264/AVC compliant decoder.
Automatic modeling and authoring of nonlinear interactions between acoustic objects

The physical synthesis of musical sounds is based on the modeling of the nonlinear interaction between two separate structures (at least one of which with desirable resonating properties). Such structures and their interaction are usually modeled with a global approach (as a single system), but flexibility and scalability issues suggest us that it would be highly desirable to adopt a block-wise approach, based on the individual synthesis and discretization of the interacting parts. In this paper we address the problem of how to automate the modeling of this nonlinear interaction and how to enable the on-the-fly fusion of model that corresponds to this interaction. We show how a solution based on binary connection trees can be fruitfully employed in an integrated modeling system that is able to automate this sound synthesis approach. We also show that, with this solution, the modeling of physical interactions can be done in an entirely symbolic (graphical) fashion. We finally provide a description of the graphical user interface for a user-friendly authoring of interactional models and an overview of a live performance system based on this technology.
Geometric reconstruction of the environment from its response to multiple acoustic emissions

In this paper we propose a method for reconstructing the 2D geometry of the surrounding environment based on the signals acquired by a fixed microphone, when a series of acoustic stimula are produced in different positions in space. After estimating the Times Of Arrival (TOAs) of the reflective paths, we turn each TOA into a projective geometric constraint that can be used for determining the locations of the reflectors. The result consists of a collection of planar surfaces that correspond to the reflectors' locations. In this paper we present the whole processing chain and prove its effectiveness through experimental results.
Fast keypoint detection in video sequences

Several computer vision tasks exploit a succinct representation of the visual content in the form of sets of local features. Given an input image, feature extraction algorithms identify keypoints and assign to each of them a descriptor, based on the characteristics of the surrounding visual content. Several tasks might require local features to be extracted from a video sequence, on a frame-by-frame basis. Although temporal downsampling has been proven to be an effective solution for mobile augmented reality and visual search, high temporal resolution is a key requirement for time-critical applications such as object tracking, event recognition, pedestrian detection, surveillance. In recent years, more and more computationally efficient visual feature detectors and descriptors have been proposed. Nonetheless, such approaches are tailored to still images. In this paper we propose a fast keypoint detection algorithm for video sequences, that exploits the temporal coherence of the sequence of keypoints. According to the proposed method, each frame is preprocessed so as to identify the parts of the input frame for which keypoint detection and description need to be performed. Our experiments show that it is possible to achieve a reduction in computational time of up to 40%, without significantly affecting the task accuracy.
Coding video sequences of visual features

Visual features provide a convenient representation of the image content, which is exploited in several applications, e.g., visual search, object tracking, etc. In several cases, visual features need to be transmitted over a bandwidth-limited network, thus calling for coding techniques to reduce the required rate, while attaining a target efficiency for the task at hand. Although the literature has recently addressed the problem of coding local features extracted from still images, in this paper we propose, for the first time, a coding architecture designed for local features extracted from video content. We exploit both spatial and temporal redundancy by means of intra-frame and inter-frame coding modes. In addition, we propose a coding mode decision based on rate-distortion optimization. Experimental results demonstrate that, in the case of SIFT descriptors, exploiting temporal redundancy leads to substantial gains in terms of coding efficiency.
Video codec identification

Video content is routinely acquired and distributed in digital format. Therefore, it is customary to have the content encoded multiple times. In this paper we consider a processing chain of two coding steps and we propose a method that aims at identifying the type of codec used in the first step, by analyzing its coding-based footprints. The method relies on the fact that lossy coding is an almost idempotent operation, i.e., re-encoding the reconstructed sequence with the same codec and coding parameters produces a sequence that is highly correlated with the input one. As a consequence, it is possible to analyze this sort of correlation to identify the first codec provided that the second codec does not introduce severe quality degradation. The proposed solution finds several applications in the field of multi-media forensics, e.g. to identify the device that generated the original video stream or detect collages of different sequences.
Tracking of two acoustic sources in reverberant environments using a particle swarm optimizer

In this paper we consider the problem of tracking multiple acoustic sources in reverberant environments. The solution that we propose is based on the combination of two techniques. A blind source separation (BSS) method known as TRINICON  is applied to the signals acquired by the microphone arrays. The TRINICON de-mixing filters are used to obtain the Time Differences of Arrival (TDOAs), which are related to the source location through a nonlinear function. A particle filter is then applied in order to localize the sources. Particles move according to a swarm-like dynamics, which significatively reduces the number of particles involved with respect to traditional particle filter. We discuss results for the case of two sources and four microphone pairs. In addition, we propose a method, based on detecting source inactivity, which overcomes the ambiguities that intrinsically arise when only two microphone pairs are used. Experimental results demonstrate that the average localization error on a variety of pseudo-random trajectories is around 40 cm when the T60 reverberation time is 0.6s.
Subjective evaluation of a NO-reference video quality Monitoring algorithm for H.264/AVC video over a noisy channel

In this paper we evaluate NORM, a NO-Reference video quality Monitoring algorithm we proposed in a previous work, for the prediction of the subjective quality of H.264/AVC video transmitted over a noisy packet-switched network. NORM produces an estimate of the mean square error distortion at the macroblock level between the noiseless and noisy sequence, without having access to the former. The output of NORM can be readily converted into a no-reference estimate of the PSNR at the sequence level. We carried out an extensive subjective evaluation campaign on CIF and 4CIF resolution sequences encoded with H.264/AVC and transmitted over a channel that drops packets at different packet loss rates, to obtain the differential mean opinion scores. Our results show that the estimated PSNR achieves good correlation with the subjective scores, very close to the ones achieved by the PSNR computed in full-reference mode, i.e. as if the noiseless sequence would be available at the decoder.
Geometric calibration of distributed microphone arrays from acoustic source correspondences

This paper proposes a method that solves the problem of geometric calibration of microphone arrays. We consider a distributed system, in which each array is controlled by separate acquisition devices that do not share a common synchronization clock. Given a set of probing sources, e.g. loudspeakers, each array computes an estimate of the source locations using a conventional TDOA-based algorithm. These observations are fused together by the proposed method, in order to estimate the position and pose of one array with respect to the other. Unlike previous approaches, we explicitly consider the anisotropic distribution of localization errors. As such, the proposed method is able to address the problem of geometric calibration when the probing sources are located both in the near- and far-field of the microphone arrays. Experimental results demonstrate that the improvement in terms of calibration accuracy with respect to state-of-the-art algorithms can be substantial, especially in the far-field.