Forensic gait analysis — Morphometric assessment from surveillance footage

© 2019 Elsevier B.V. Following the technological rise of surveillance cameras and their subsequent proliferation in public places, the use of information gathered by such means for investigative and evaluative purposes sparked a large interest in the forensic community and within policing scenarios. In particular, it is suggested that analysis of the body, especially the assessment of gait characteristics, can provide useful information to aid the investigation. This paper discusses the influences upon gait to mitigate some of the limitations of surveillance footage, including those due to the varying anatomical differences between individuals. Furthermore, the differences between various techniques applied to assess gait are discussed, including biometric gait recognition, forensic gait analysis, tracking technology, and marker technology. This review article discusses the limitations of the current methods for assessment of gait; exposing gaps within the literature in regard to various influences impacting upon the gait cycle. Furthermore, it suggests a ‘morphometric’ technique to enhance the available procedures to potentially facilitate the development of standardised protocols with supporting statistics and database. This in turn will provide meaningful information to forensic investigation, intelligence-gathering processes, and potentially as an additional method of forensic evaluation of evidence

Automatic execution of expressive music performance

The definition of computer models to represent the expressiveness of a musical performance, is useful to try to understand how and what way anyone can express expressive intentions in a music performance. The CaRo 2.0 is a computer model or software system that allows automatic computation in interactive way for rendering expressive musical scores. Initially, the exclusively on Microsoft environment, which limits the interest of the product. This thesis relates to the porting and integrationope

Third International Conference on Technologies for Music Notation and Representation TENOR 2017

The third International Conference on Technologies for Music Notation and Representation seeks to focus on a set of specific research issues associated with Music Notation that were elaborated at the first two editions of TENOR in Paris and Cambridge. The theme of the conference is vocal music, whereas the pre-conference workshops focus on innovative technological approaches to music notation

Matchmakers or tastemakers? Platformization of cultural intermediation & social media’s engines for ‘making up taste’

There are long-standing practices and processes that have traditionally mediated between the processes of production and consumption of cultural content. The prominent instances of these are: curating content by identifying and selecting cultural content in order to promote to a particular set of audiences; measuring audience behaviours to construct knowledge about their tastes; and guiding audiences through recommendations from cultural experts. These cultural intermediation processes are currently being transformed, and social media platforms play important roles in this transformation. However, their role is often attributed to the work of users and/or recommendation algorithms. Thus, the processes through which data about users’ taste are aggregated and made ready for algorithmic processing are largely neglected. This study takes this problematic as an important gap in our understanding of social media platforms’ role in the transformation of cultural intermediation. To address this gap, the notion of platformization is used as a theoretical lens to examine the role of users and algorithms as part of social media’s distinct data-based sociotechnical configuration, which is built on the so-called ‘platform-logic’. Based on a set of conceptual ideas and the findings derived through a single case study on a music discovery platform, this thesis developed a framework to explain ‘platformization of cultural intermediation’. This framework outlines how curation, guidance, and measurement processes are ‘plat-formed’ in the course of development and optimisation of a social media platform. This is the main contribution of the thesis. The study also contributes to the literature by developing the concept of social media’s engines for ‘making up taste’. This concept illuminates how social media operate as sociotechnical cultural intermediaries and participates in tastemaking in ways that acquire legitimacy from the long-standing trust in the objectivity of classification, quantification, and measurement processes

Measuring Expressive Music Performances: a Performance Science Model using Symbolic Approximation

Music Performance Science (MPS), sometimes termed systematic musicology in Northern Europe, is concerned with designing, testing and applying quantitative measurements to music performances. It has applications in art musics, jazz and other genres. It is least concerned with aesthetic judgements or with ontological considerations of artworks that stand alone from their instantiations in performances. Musicians deliver expressive performances by manipulating multiple, simultaneous variables including, but not limited to: tempo, acceleration and deceleration, dynamics, rates of change of dynamic levels, intonation and articulation. There are significant complexities when handling multivariate music datasets of significant scale. A critical issue in analyzing any types of large datasets is the likelihood of detecting meaningless relationships the more dimensions are included. One possible choice is to create algorithms that address both volume and complexity. Another, and the approach chosen here, is to apply techniques that reduce both the dimensionality and numerosity of the music datasets while assuring the statistical significance of results. This dissertation describes a flexible computational model, based on symbolic approximation of timeseries, that can extract time-related characteristics of music performances to generate performance fingerprints (dissimilarities from an ‘average performance’) to be used for comparative purposes. The model is applied to recordings of Arnold Schoenberg’s Phantasy for Violin with Piano Accompaniment, Opus 47 (1949), having initially been validated on Chopin Mazurkas.1 The results are subsequently used to test hypotheses about evolution in performance styles of the Phantasy since its composition. It is hoped that further research will examine other works and types of music in order to improve this model and make it useful to other music researchers. In addition to its benefits for performance analysis, it is suggested that the model has clear applications at least in music fraud detection, Music Information Retrieval (MIR) and in pedagogical applications for music education

Semantic Audio Analysis Utilities and Applications.

PhDExtraction, representation, organisation and application of metadata about audio recordings are in the concern of semantic audio analysis. Our broad interpretation, aligned with recent developments in the field, includes methodological aspects of semantic audio, such as those related to information management, knowledge representation and applications of the extracted information. In particular, we look at how Semantic Web technologies may be used to enhance information management practices in two audio related areas: music informatics and music production. In the first area, we are concerned with music information retrieval (MIR) and related research. We examine how structured data may be used to support reproducibility and provenance of extracted information, and aim to support multi-modality and context adaptation in the analysis. In creative music production, our goals can be summarised as follows: O↵-the-shelf sound editors do not hold appropriately structured information about the edited material, thus human-computer interaction is inefficient. We believe that recent developments in sound analysis and music understanding are capable of bringing about significant improvements in the music production workflow. Providing visual cues related to music structure can serve as an example of intelligent, context-dependent functionality. The central contributions of this work are a Semantic Web ontology for describing recording studios, including a model of technological artefacts used in music production, methodologies for collecting data about music production workflows and describing the work of audio engineers which facilitates capturing their contribution to music production, and finally a framework for creating Web-based applications for automated audio analysis. This has applications demonstrating how Semantic Web technologies and ontologies can facilitate interoperability between music research tools, and the creation of semantic audio software, for instance, for music recommendation, temperament estimation or multi-modal music tutorin