Dumitru Stanomir

A robust mathematical model for simulating wrinkle activity in 3D facial animations

In this paper we present a novel mathematical model for simulating wrinkle activity in 3D facial animations. We use a series of linked muscle segments that we call cordon muscles in order to model facial contractions. The affected vertices are interpolated towards their contraction targets across the object surface using a Hermite spline interpolation approach, while the interpolation weights are computed using trigonometrical functions. Skin bulges and wrinkles induced by contractions are simulated using a proposed modified form of the Rayleigh distribution function. The efficiency of the model proposed in this paper was proved by testes on various 3D surfaces with different curvature features. Our model helps enhancing facial expression realism while performing 3D facial animations.

Robust audio forensic software for recovering speech signals drowned in loud music

Audio evidence, when accepted by the court, can decide the final verdict in a trial. In order to be evaluated, these materials must be authenticated, but also the intelligibility of the message must be undoubtable. Two main categories of multimedia forensics solve these problems: content authentication and noise reduction. The application presented in this paper is part of the latter category. In order to conceal a conversation, the first action that comes into mind is also the easiest one: turn loud a nearby audio source. Since the most available audio sources play musical materials, if a microphone was placed in the room, it would record the speech signal heavily masked by music. A classical adaptive filtering method could be applied to recover the speech only if the speakers and the musical source remain perfectly still or, in other words, the acoustic environment does not change in time. This ideal situation is not to be found very often in real situations. This paper presents a method for recovering speech signals masked by loud music that is robust to acoustic environment variations. The method is thoroughly described, tested, and compared with a solution based on the recursive least-squares (RLS) adaptive algorithm using a variable forgetting factor.

Development and testing of an audio forensic software for enhancing speech signals masked by loud music

In many situations audio recordings can decide the fate of a trial when accepted as evidence. But until they can be taken into account they must be authenticated at first, but also the quality of the targeted content (speech in most cases) must be good enough to remove any doubt. In this scope two main directions of multimedia forensics come into play: content authentication and noise reduction. This paper presents an application that is included in the latter. If someone would like to conceal their conversation, the easiest way to do it would be to turn loud the nearest audio system. In this situation, if a microphone was placed close by, the recorded signal would be apparently useless because the speech signal would be masked by the loud music signal. The paper proposes an adaptive filters based solution to remove the musical content from a previously described signal mixture in order to recover the masked vocal signal. Two adaptive filtering algorithms were tested in the proposed solution: the Normalised Least Mean Squares (NLMS) and Recursive Least Squares (RLS). Their performances in the described situation were evaluated using Simulink, compared and included in the paper.

Electrical network signal's waveform and frequency logging for forensic

In this paper we develop a framework for collecting the ENF (electric network frequency) variations in a database, which can be used in digital media authentication and time stamping. The proposed framework allows the recording of the ENF variations and of the hum signal. The discontinuities introduced in the hum signal by the probe used for data acquisition are studied and methods for minimizing these discontinuities are proposed. In the end a method for time stamping audio recordings is used, based on the created ENF database.

Analysis of reverberation time blind estimation used in audio forensics

This paper proposes an analysis of the possibility to use the reverberation time as a reliable tool in audio forensics, for detecting audio editing traces in a recording. We begin with an optimized method for the blind estimation of the reverberation time, in the presence of additive noise and we further adapt it to better serve the forensic context. Next we present several experiments which validate, through objective measurements, the estimation method we used. Finally we propose different scenarios in which we underline the opportunity to use reverberation time as a mean of detecting audio editing in a recording. The results of our incipient study showed that, within controlled conditions, the reverberation time parameter can be successfully used for detecting the existence of audio editing traces in a recording.

Low cost electric network signal and frequency recorder

This paper presents a low cost solution for a framework used for recording the electric network signal and for logging the fundamental frequency variations. The resulted database is used for time stamping audio recordings based on the Pearson correlation coefficient. Furthermore, we propose a fast algorithm for computing the Pearson correlation coefficient by emplying filters to implement efficiently mathematical operations involved in the process. The overall cost of the proposed framework is reduced ten times than its previous version.

Investigation on a Multimedia Forensic Noise Reduction Method Based on Proportionate Adaptive Algorithms

In the modern era, audio or video recording is at everyone’s disposal any time with very low costs. Technology advances allow cameras and microphones to be installed in the most casual accessories like eyeglasses or clothes. Moreover, multimedia editing is also massively available. Near professional forgeries can be made using free software. Given the aforementioned conditions, it is understandable why multimedia forensics is a topic of great importance nowadays. The paper presents the performances obtained by using proportionate adaptive algorithms in a forensic noise reduction application, i.e., recovering a speech signal drowned in loud music, and argues why these algorithms could be preferred in such application.

Investigation on the performances of APA in forensic noise reduction

Multimedia files, either video or audio, could greatly influence the final verdict of a trial when accepted as evidence. The abundance of free editing software available nowadays make forgeries a very easy operation. Audio messages, even if authentic, in some cases, can be heavily masked by other signals and declared unusable. This paper presents the investigations on the performance of the affine projection algorithm (APA) in recovering a speech signal drowned in a loud musical signal and it represents a contribution to the multimedia forensic domain. The APA was tested in multiple situations showing the top performance limits and how the working parameters influence those limits.

Fast algorithm for detecting butt-spliced edits

In this paper we conduct an in-depth analysis of a reference method used for the detection of butt-spliced edits. First, we bring forward a solution for significantly reducing the involved time resources. Next, we reveal the methods limitations in terms of variable analysis window and we test two methods for differentiating between tampered audio signals and clean signals. We also develop a relevant experimental setup which allows us to quantify for the first time the methods performances, in the context of audio forensic.

Modelling and simulation of a high-voltage direct current ballistic circuit breaker

Interrupting a DC high power line is a very challenging task since the key element that greatly simplifies the problem in a similar AC case, which is the zero crossing of the current, is missing. The consequence of the current interruption is the occurrence of an electrical arc which must be safely extinguished. In HVDC (high-voltage direct current) applications the currents that need to be interrupted have very large values and, in addition, the power lines have a notable inductance making the extinguishing operation a serious issue if the breaking is done directly to open circuit, especially if there is a short circuit type of fault at the consumer end of the power line. A ballistic breaker gradually introduces resistors in series with the load, avoiding troublesome large current jumps, in order to achieve a smoothly interruption. Since this type of circuit breaker is relatively new, introduced in 2011, its modelling and simulation is still an up-to-date topic. The paper presents two models for a ballistic breaker, one MATLAB-Simulink model and one SPICE model which can be used to investigate and perfect the device, and also presents the simulation results for various parameters and implementation variants, highlighting strengths and weaknesses.