A framework for forensic face recognition based on recognition performance calibrated for the quality of image pairs

Recently, it has been shown that performance of a face recognition system depends on the quality of both face images participating in the recognition process: the reference and the test image. In the context of forensic face recognition, this observation has two implications: a) the quality of the trace (extracted from CCTV footage) constrains the performance achievable using a particular face recognition system; b) the quality of the suspect reference set (to which the trace is matched against) can be judiciously chosen to approach optimal recognition performance under such a constraint. Motivated by these recent findings, we propose a framework for forensic face recognition that is based on calibrating the recognition performance for the quality of pairs of images. The application of this framework to several mock-up forensic cases, created entirely from the MultiPIE dataset, shows that optimal recognition performance, under such a constraint, can be achieved by matching the quality (pose, illumination, and, imaging device) of the reference set to that of the trace. This improvement in recognition performance helps reduce the rate of misleading interpretation of the evidence

Forensic speaker recognition

The aim of forensic speaker recognition is to establish links between individuals and criminal activities, through audio speech recordings. This field is multidisciplinary, combining predominantly phonetics, linguistics, speech signal processing, and forensic statistics. On these bases, expert-based and automatic approaches have been developed to analyze the speaker's utterances on recordings, usually originating from anonymous calls, wiretapping procedures, and covert audio surveillance. Most of the forensic laboratories still opt for either of these two approaches, even though, in many respects, they appear to be complementary. The main requirements for these methods are independence to the text, ability to handle minimal length recordings, and a superior robustness regarding noise, transmission channels, and other variations of the recording conditions. Forensic speaker recognition can be considered a forerunner in the implementation of a logical inference framework to estimate the value of the evidence from the analytical results. The limits of forensic speaker recognition are the absence of a fixed and known number of highly discriminatory features in speech, the limited quality of the audio recordings captured in forensic conditions, and the application of recognition approaches in the absence of any known underlying model that accurately represents the speaker-dependent information

Theoretical and Computational Chemistry

Computer-based and theoretical approaches to chemical problems can provide atomistic understanding of complex processes at the molecular level. Examples ranging from rates of ligand-binding reactions in proteins to structural and energetic investigations of diastereomers relevant to organo-catalysis are discussed in the following. They highlight the range of application of theoretical and computational methods to current questions in chemical research

Friction ridge skin - Automated Fingerprint Identification System (AFIS)

This contribution describes the development and the forensic use of automated fingerprint identification systems (AFISs). AFISs were initially developed in order to overcome the limitations of the paper-based fingerprint collections, by digitizing the ten-print cards in computerized databases and to translate the manual pattern classification into computer-friendly codes. Then, technologies to automate the fingerprint feature extraction and comparison were developed, and AFISs were implemented on a large scale in order to improve the process of identification of repetitive offenders based on the ten-print cards. Further development of the fingerprint biometric technology allowed for the inclusion of palmprint reference databases and for the processing of fingermarks and palmmarks with, as a result, the partial automation of the forensic investigation and intelligence process. In the field of AFIS, the challenges for the future call for further automation of the feature extraction from low-quality fingerprint and fingermark images, for more transparency in the processes, for the improvement of the interoperability of the systems on a global level and the combination of biometric modalities as well as for the use of fingerprint biometric technology and scientific methodology, to further develop the forensic friction ridge evaluation process

Computational Vibrational Spectroscopy

Vibrational spectroscopy is a powerful technique to characterize the near-equilibrium dynamics of molecules in the gas and the condensed phase. This contribution summarizes efforts from computer-based methods to gain insight into the relationship between structure and spectroscopic response. Methods for this purpose include physics-based and machine-learned energy functions, and methods that separate sampling conformational space and determining the data for spectral analysis such as map-based techniques

Higher order multipole moments for molecular dynamics simulations

In conventional force fields, the electrostatic potential is represented by atom-centred point charges. This choice is in principle arbitrary, but technically convenient. Point charges can be understood as the first term of multipole expansions, which converge with an increasing number of terms towards the accurate representation of the molecular potential given by the electron density distribution. The use of multipole expansions can therefore improve the force field accuracy. Technically, the implementation of atomic multipoles is more involved than the use of point charges. Important points to consider are the orientation of the multipole moments during the trajectory, conformational dependence of the atomic moments and stability of the simulations which are discussed her