What Else Does Your Biometric Data Reveal? A Survey on Soft Biometrics

Abstract

Recent research has explored the possibility of extracting ancillary information from primary biometric traits, viz., face, fingerprints, hand geometry and iris. This ancillary information includes personal attributes such as gender, age, ethnicity, hair color, height, weight, etc. Such attributes are known as soft biometrics and have applications in surveillance and indexing biometric databases. These attributes can be used in a fusion framework to improve the matching accuracy of a primary biometric system (e.g., fusing face with gender information), or can be used to generate qualitative descriptions of an individual (e.g., "young Asian female with dark eyes and brown hair"). The latter is particularly useful in bridging the semantic gap between human and machine descriptions of biometric data. In this paper, we provide an overview of soft biometrics and discuss some of the techniques that have been proposed to extract them from image and video data. We also introduce a taxonomy for organizing and classifying soft biometric attributes, and enumerate the strengths and limitations of these attributes in the context of an operational biometric system. Finally, we discuss open research problems in this field. This survey is intended for researchers and practitioners in the field of biometrics.

Soft biometric retrieval to describe and identify surveillance images

“…Nixon et al and Dantcheva et al provide comprehensive surveys exploring the topic of soft biometrics [19,4]. Earlier soft biometric studies focus on annotating a set of absolute categorical labels, analysing the mutual exclusivity and identifying ability of each soft trait [25,5].…”

“…Unlike traditional hard biometrics, soft biometrics are formed as a collection of human describable, distinguishing visual features [19,5,4]. Soft traits (e.g gender, height etc.)…”

Analysing comparative soft biometrics from crowdsourced annotations

“…Two recent surveys explore the field in detail, reviewing techniques for demographic estimation from face, body, clothing and other modalities such as gait, fingerprint and iris [30,5]. Nixon et al discuss the evolution of soft biometrics from the original Bertillonage, to the search for discriminative measures and their estimation from surveillance imagery.…”

“…The survey defines the area as "the estimation or use of personal characteristics describable by humans that can be used to aid or effect person recognition" [30]. Dantcheva et al introduce a taxonomy for organising soft biometrics attributes and highlight the benefits of soft biometrics as a human understandable interpretation for video surveillance, providing robustness to low quality images and consent-free acquisition [5].…”

“…Soft biometrics are a new form of biometric that fill in these information gaps, as they rely only on human perception and description to systematically label subjects [30,5]. They have been shown to be objective, salient, reliable and robust to changes in distance [39,36].…”