Varieties of biometric facial techniques for detecting offenders

Many crimes are committed where the only record of the event is in the memory of a witness or victim. Recovering a recognisable image of the offender’s face is then crucial for solving the crime. Traditionally, eyewitnesses describe the offender’s face and select individual facial features – eyes, hair, nose, etc. – to build a ‘composite’. This image is then published in the media so that someone can recognise it and phone the police with a name. Unfortunately, when tested using life-like procedures, this method rarely produces recognisable images. The current paper describes these systems for extracting such biometric information from witnesses. It also describes how useful they are and explores three such approaches for improving their effectiveness. Included are a new method to interview witnesses (a holistic-cognitive interview), a new method to present images to the public (animated composite) and a new system to construct the face (EvoFIT)

Wheat and barley leaf diseases – the Saskatchewan situation

Non-Peer Reviewe

Towards a comprehensive 3D dynamic facial expression database

Human faces play an important role in everyday life, including the expression of person identity, emotion and intentionality, along with a range of biological functions. The human face has also become the subject of considerable research effort, and there has been a shift towards understanding it using stimuli of increasingly more realistic formats. In the current work, we outline progress made in the production of a database of facial expressions in arguably the most realistic format, 3D dynamic. A suitable architecture for capturing such 3D dynamic image sequences is described and then used to record seven expressions (fear, disgust, anger, happiness, surprise, sadness and pain) by 10 actors at 3 levels of intensity (mild, normal and extreme). We also present details of a psychological experiment that was used to formally evaluate the accuracy of the expressions in a 2D dynamic format. The result is an initial, validated database for researchers and practitioners. The goal is to scale up the work with more actors and expression types

EvoFIT: A Holistic, Evolutionary Facial Imaging System

This thesis details the development and evaluation of a new photofitting approach. The motivation for this work is that current photofit systems used by the police - whether manual or computerized - do not appear to work very well. Part of the problem with these approaches is they involve a single facial representation that necessitates a verbal interaction. When a multiple presentation is considered, our innate ability to recognize faces is capitalized (and the potentially disruptive effect of the verbal component is reduced). The approach works by employing Genetic Algorithms to evolve a small group of faces to be more like a desired target. The main evolutionary influence is via user input that specifies the similarity of the presented images with the target under construction. The thesis follows three main phases of development. The first involves a simple system modelling the internal components of a face (eyes, eyebrows, nose and mouth) containing features in a fixed relationship with each other. The second phase applies external facial features (hair and ears) along with an appropriate head shape and changes in the relationship between features. That the underlying model is based on Principal Components Analysis captures the statistics of how faces vary in terms of shading, shape and the relationship between features. Modelling was carried out in this way to create more realistic looking photofits and to guard against implausible featural relationships possible with traditional approaches. The encouraging results of these two sections prompted the development of a full photofit system: EvoFIT. This software is shown to have continued promise both in the lab and in a real case. Future work is directed particularly at resolving issues concerning the anonymity of the database faces and the creation of photofits from the subject's memory of a target

Accuracy of relational and featural information in facial-composite images

Facial-composite images are crucial in helping to bring perpetrators to justice and thereby maintain national and international security. Psychology can assist in identifying the accuracy of such facial information as well as ways to improve their identification rates. The current experiment demonstrates that composites tend to differ in terms of their accuracy of featural information (individual facial features) and relational information (spacing between those facial features) depending on the type of composite software used. Composites constructed with feature systems tend to have more-accurate feature information, whilst those constructed with holistic systems tend to have more-accurate relational information. Further, it was found that not only the addition of sunglasses on poor-quality composites, but also viewing composites from the side, can increase their identifiability. This could be applied by the police to potentially increase identification and arrest rates of perpetrators

Configural and featural information in facial-composite images

Eyewitnesses are often invited to construct a facial composite, an image created of the person they saw commit a crime that is used by law enforcement to locate criminal suspects. In the current paper, the effectiveness of composite images was investigated from traditional feature systems (E-FIT and PRO-fit), where participants (face constructors) selected individual features to build the face, and a more recent holistic system (EvoFIT), where they ‘evolved' a composite by repeatedly selecting from arrays of complete faces. Further participants attempted to name these composites when seen as an unaltered image, or when blurred, rotated, linearly stretched or converted to a photographic negative. All of the manipulations tested reduced correct naming of the composites overall except (i) for a low level of blur, for which naming improved for holistic composites but reduced for feature composites, and (ii) for 100% linear stretch, for which a substantial naming advantage was observed. Results also indicated that both featural (facial elements) and configural (feature spacing) information was useful for recognition in both types of composite system, but highly-detailed information was more accurate in the feature-based than the holistic method. The naming advantage of linear stretch was replicated using a forensically more-practical procedure with observers viewing an unaltered ¬composite sideways. The work is valuable to police practitioners and designers of facial-composite systems

Interviewing techniques for Darwinian facial-composite systems.

Eyewitnesses are often asked to describe the appearance of an offender’s face, normally as part of a cognitive interview (CI), and then to construct a facial composite of it by selecting hair, eyes, nose, etc. Recent research indicates that facial composites of this type are rendered much-more identifiable when constructors focus on global character (holistic) judgements of the face after having recalled it in detail. Here, we investigated whether components of this so-called ‘holistic’ CI (H-CI) were applicable to newer ‘evolving’ (Darwinian) methods of face construction. We found that the face description component of the interview promoted better-quality composites than the holistic component, but the most-identifiable composites emerged when both components were used together in the same interview as an H-CI. Composites were also more identifiable following description of all features of the face than an alternative involving description of hair. Implications are discussed for real-world face-construction using evolving systems

Tell me again about the face: Using repeated interviewing techniques to improve feature-based facial composite technologies

Facial composite technologies are used to produce visual resemblances of an offender. However, resemblances may be poor, particularly when composites are constructed using traditional `feature' composite systems deployed several days after the crime. In this case a witness may have forgotten important details about an offender's appearance. Engaging in early and repeated retrieval attempts could potentially overcome this issue. Experiment 1 showed that more recognisable feature composites were produced after participants had provided detailed face recall during two supported retrieval attempts, which included instructions to reinstate the context in which the target had been seen, free recall and cued recall. The first recall attempt was completed on the same day as viewing the target individual, and the second two days later, and immediately before composite construction (traditional forensic procedure). Experiment 2 showed that repeated interviewing only incurred a benefit when the same day interview provided ample retrieval support. The results suggest how traditional forensic procedures can be easily modified to improve the quality of feature composites, and thereby facilitate the detection of offenders

Interviewing and visualisation techniques: Attempting to further improve EvoFIT facial composites

Victims of and witnesses to crime are asked to describe an offender using cognitive interviewing techniques (CI), before constructing a visual likeness of the face. The aim of the current experiment was to investigate whether composite construction using the EvoFIT holistic system would benefit from the parallel use of three enhancement techniques. The study manipulated the type of interview used to elicit a face description (CI vs. holistic cognitive interview, or H-CI) and trialled a visualisation technique for selecting faces (no visualisation vs. visualisation of external features). Also included was a new construction procedure for EvoFIT that requested constructors to focus on the region around the eyes when making face selections. Based on past research, it was anticipated that both the H-CI and external-feature visualisation would promote construction of a more identifiable composite (compared to when each technique was not used). Rather unexpectedly, the results revealed that neither technique improved correct naming of composites, yet an interaction was observed: visualisation of external features led to a benefit that approached significance when used in conjunction with the H-CI (cf. CI). However, when no external-feature visualisation was used, composites were better named following the more usual CI (cf. H-CI) protocol. Results are promising for the new method of face selection, which was used by all participants (focusing on the eye region). Indeed, in the baseline condition, where this was the only `enhancement' method used, naming of composites was 55% correct. Arguably, focusing on the character of the face during the H-CI may instate a processing style that is not well aligned with the new procedure of selecting faces according to the eye region. To overcome this misalignment of processing stages, we propose to ask constructors to focus on this region of the face during the H-CI itself. Implications for theory and police practice are discussed

Facial Recall and Computer Composites

Imagine, if you will, that you are sitting quietly outside a café sipping your favourite hot beverage when someone rushes past and snatches your mobile phone, which you left on the table, as you often do. You were able to get a good look at the person’s face, albeit for a short time. Your next hour is spent speaking with a police officer giving a description of what happened and what the offender looked like. It is likely that you could describe accurately what happened. You will probably also be able to describe the perpetrator’s build and clothing. There should be no trouble in saying what was the sex of the person and his or her ethnicity; you should be reasonably accurate at estimating the age, height and weight. You could probably remember some details of the person’s face. Incidents such as these are known as “volume” crime. They occur frequently, often without physical assault to the victim, and their seriousness, at least from a legal perspective, is fairly minor. Due to limitations in police resources, many perpetrators of volume crime are never caught, although time spent locating particularly prolific offenders can be worthwhile. Crimes involving these repeat offenders, and other crimes of a more serious nature including murder, arson and rape, are generally given higher priority in police investigations. It is in these cases that eyewitnesses (witnesses or victims) may be asked to engage in a range of tasks to assist in the detection and later conviction of the offender. When the police have a suspect, they may be asked to take part in an identification parade. (Further details about this are the focus of a separate chapter.) Alternatively, eyewitnesses may be shown photographs of previously arrested criminals for identification, sometimes referred to as mugshots. In the absence of a suspect, CCTV footage or other evidence, witnesses may be called upon to externalise an offender’s face. The aim is to create a visual image based on remembered information, so that it can be shown to other people for identification. Such images are known as facial composites and are seen in the newspapers and on TV, for example, BBC CrimeWatch. The idea is that someone who is familiar with the face will name it to the police and, in doing so, will provide new lines of enquiry. The focus of the current chapter is on the construction and the recognition of facial composites produced by modern software systems. A separate chapter in this volume details how composites are created by sketch artists. This chapter describes and evaluates typical software programs that the police use to construct faces. It will be demonstrated that the traditional approach used with eyewitnesses is generally ineffective for producing identifiable images, and that alternatives are required if composites are to be effective in the battle against crime. Several successful developments are described. The final section looks to the future and asks what might be on the horizon for producing even more effective faces