Soft biometrics for subject identification using clothing attributes

Recently, soft biometrics has emerged as a novel attribute-based person description for identification. It is likely that soft biometrics can be deployed where other biometrics cannot, and have stronger invariance properties than vision-based biometrics, such as invariance to illumination and contrast. Previously, a variety of bodily soft biometrics has been used for identifying people. Describing a person by their clothing properties is a natural task performed by people. As yet, clothing descriptions have attracted little attention for identification purposes. There has been some usage of clothing attributes to augment biometric description, but a detailed description has yet to be used. We show here how clothing traits can be exploited for identification purposes. We explore the validity and usability of a set of proposed semantic attributes. Human identification is performed, evaluated and compared using different proposed forms of soft clothing traits in addition and in isolation

From clothing to identity; manual and automatic soft biometrics

Soft biometrics have increasingly attracted research interest and are often considered as major cues for identity, especially in the absence of valid traditional biometrics, as in surveillance. In everyday life, several incidents and forensic scenarios highlight the usefulness and capability of identity information that can be deduced from clothing. Semantic clothing attributes have recently been introduced as a new form of soft biometrics. Although clothing traits can be naturally described and compared by humans for operable and successful use, it is desirable to exploit computer-vision to enrich clothing descriptions with more objective and discriminative information. This allows automatic extraction and semantic description and comparison of visually detectable clothing traits in a manner similar to recognition by eyewitness statements. This study proposes a novel set of soft clothing attributes, described using small groups of high-level semantic labels, and automatically extracted using computer-vision techniques. In this way we can explore the capability of human attributes vis-a-vis those which are inferred automatically by computer-vision. Categorical and comparative soft clothing traits are derived and used for identification/re identification either to supplement soft body traits or to be used alone. The automatically- and manually-derived soft clothing biometrics are employed in challenging invariant person retrieval. The experimental results highlight promising potential for use in various applications

Performing content-based retrieval of humans using gait biometrics

In order to analyse surveillance video, we need to efficiently explore large datasets containing videos of walking humans. Effective analysis of such data relies on retrieval of video data which has been enriched using semantic annotations. A manual annotation process is time-consuming and prone to error due to subject bias however, at surveillance-image resolution, the human walk (their gait) can be analysed automatically. We explore the content-based retrieval of videos containing walking subjects, using semantic queries. We evaluate current research in gait biometrics, unique in its effectiveness at recognising people at a distance. We introduce a set of semantic traits discernible by humans at a distance, outlining their psychological validity. Working under the premise that similarity of the chosen gait signature implies similarity of certain semantic traits we perform a set of semantic retrieval experiments using popular Latent Semantic Analysis techniques. We perform experiments on a dataset of 2000 videos of people walking in laboratory conditions and achieve promising retrieval results for features such as Sex (mAP= 14% above random), Age (mAP=10% above random) and Ethnicity (mAP=9% above random

Modeling Errors in Biometric Surveillance and De-duplication Systems

In biometrics-based surveillance and de-duplication applications, the system commonly determines if a given individual has been encountered before. In this dissertation, these applications are viewed as specific instances of a broader class of problems known as Anonymous Identification. Here, the system does not necessarily determine the identity of a person; rather, it merely establishes if the given input biometric data was encountered previously. This dissertation demonstrates that traditional biometric evaluation measures cannot adequately estimate the error rate of an anonymous identification system in general and a de-duplication system in particular. In this regard, the first contribution is the design of an error prediction model for an anonymous identification system. The model shows that the order in which individuals are encountered impacts the error rate of the system. The second contribution - in the context of an identification system in general - is an explanatory model that explains the relationship between the Receiver Operating Characteristic (ROC) curve and the Cumulative Match Characteristic (CMC) curve of a closed-set biometric system. The phenomenon of biometrics menagerie is used to explain the possibility of deducing multiple CMC curves from the same ROC curve. Consequently, it is shown that a good\u27\u27 verification system can be a poor\u27\u27 identification system and vice-versa.;Besides the aforementioned contributions, the dissertation also explores the use of gait as a biometric modality in surveillance systems operating in the thermal or shortwave infrared (SWIR) spectrum. In this regard, a new gait representation scheme known as Gait Curves is developed and evaluated on thermal and SWIR data. Finally, a clustering scheme is used to demonstrate that gait patterns can be clustered into multiple categories; further, specific physical traits related to gender and body area are observed to impact cluster generation.;In sum, the dissertation provides some new insights into modeling anonymous identification systems and gait patterns for biometrics-based surveillance systems

Análisis espacial y prognosis de la seguridad en entornos urbanos : comprensión de la trazabilidad de la conducta espacial y de su vínculo con las fuerzas motrices de la seguridad

Tesis de la Universidad Complutense de Madrid, Facultad de Geografía e Historia, Departamento de Geografía Humana, leída el 30-01-2018Currently, our societies demand a permanent and trustable security. The number and typologyof threats that they are facing on daily basis can lead to their eminent collapse. The ground of theabove-mentioned status quo is simple: a security applied en mass is based on a fallacies and myths.This mythical security puts on risk much more than an ordinary clash between theoretical securitymodels: the entire social peace system is questioned. Transversally to those threats is proposed thetraceability concept, frequently used in bioscience and biometric technologies, but not in commonuse for spatial analysis purposes. Within this unprecedented research founded in the field of thespatial analysis, we will analyze the main security driving forces existing in our societies - from amulti-scale perspective - with the aim to achieve a final social improvement.The doctoral thesis presented herein covers a comprehensive pursuit of the spatial conductbehaviour and its traceability. In this thesis, focused on urban areas, it will be analyzed how thecontemporary surveillance technologies work, evaluating whether those technologies and massprograms are covering the security demanded by the societies. Within the following chapters we willreview how modern security have intentionally designed and developed a smokescreen that istricking a true pragmatic security and which is creating an unprecedented security failure. Once thissmokescreen is revealed and questioned, the results are demonstrating minimal capabilities of itsapplication and profitability for traceability purposes. What we presented herein, is not exclusively ameta-theoretical analysis of a state of art...Actualmente, nuestras sociedades demandan un estado permanente y verificable de seguridad.Los riesgos y amenazas a los que nos enfrentamos a diario pueden constituir el punto deinflexión que derive a nuestras sociedades - tal y como las conocemos y comprendemos - hacia uncolapso inminente. Los motivos de dicho status quo son simples: la seguridad - como producto - aplicadaen masa se fundamenta en un arquetipo de falacias y mitos. A pesar de que objetivamente sonindiscutibles las capacidades de vigilia tecnológica actual, la ratio volumen- eficiencia es sumamentecuestionable. Consecuentemente, el producto resultante adquirido - la seguridad como garantía de lapaz y orden social - pone en riesgo mucho más que una mera confrontación entre planteamientosmeta-teóricos: el conjunto de paz y garantías sociales vigentes en nuestra sociedad está en riesgo.Transversalmente al conjunto de riesgos y amenazas presentes nos encontramos con elconcepto de la trazabilidad, frecuentemente usado en ciencias naturales y tecnologías vinculadas alanálisis biométrico, pero raramente asociado al análisis espacial. Durante la presente investigación,de la cual no existen precedentes en cuanto al tratamiento de la temática, nos centraremos en el análisisde las fuerzas motrices vinculadas a la seguridad – desde una perspectiva multiescalar – con elobjetivo de aportar un beneficio social...Depto. de GeografíaFac. de Geografía e HistoriaTRUEunpu