This research involves the inter-comparison of 34 pairs of New Balance model 878 shoes that were worn by the same person, running the same distance, on the same type of surface with ground truth information.
This research is investigating the application of a 3D structured light scanner to recover impression evidence from the crime scene. Some of the perceived benefits of using this technology would be that the evidence would be recovered in a non-contact manner. Also the acquisition of the evidence will be much quicker than using traditional casting methods.
Significant advances in learning outcomes are being demanded of all forensic disciplines. This is particularly true of the forensic identification sciences, including the analysis and assessment of footwear impression evidence. In 2009, the National Academy of Sciences reported a deficit in knowledge concerning the evidentiary value of forensic shoeprint impressions (NAS 2009). The conclusions of this review body support continued studies to extend knowledge concerning the statistical assessment of similarity, and the relative frequency of class and accidental characteristics present in various populations. To address these mandates, the proposed project asserts that an appropriately constructed research study can have a 4-fold impact on the field of shoeprint impression evidence.
Asymmetrical changes in shoes and shoeprint evidence can be caused by medical conditions in pairs of shoes with similar time worn (e.g., a different degree of wear on the insole can be caused by dysfunctions in the excretory system). This project examines the effects of different medical conditions in asymmetrical findings in shoes and shoeprint evidence.
A European consortium is developing a mobile handheld high-resolution 3D scanner and 3D data analysis software for the recovery and analysis of footwear and tire impression evidence.
The proposed project is to develop a novel and portable high-resolution (e.g., 600 dots per inch, or dpi) optical 3D scanning system to measure shoe or tire impressions. The 3D imaging technique is based on the binary defocusing technique and the auto-exposure control method that were recently invented by our team. Preliminary study has demonstrated that this approach permits camera-pixel-resolution 3D imagery capture and enables precise timing control, and thus has the potential to achieve sufficient accuracy and resolution for capturing shoe or tire impression in both snow and soil.
It has long been anecdotally observed that there can be a difference in physical dimensions between static and dynamic test impressions. The researchers have taken both static and dynamic test impressions from 90 pairs of shoes (360 test impressions). They will take five measurements (1800 measurements) from each impression to determine if this observation is accurate. In addition the researchers will attempt to determine if any difference is correlated with shoe style. The authors have broken each pair into one of three broad styles – flat bottom/continuous sole, non-continuous (shallowly recessed mid portion) athletic shoes and shoes/boots with a defined/stepped heel.
Although it is well-recognized that criminals track dusts to and from every crime scene, dust particles on a suspects shoes are very seldom used as evidence linking the accused to the crime. The major obstacle preventing the use of this type of evidence is that the shoes have mixtures of particles arising from activity before, during and after the crime itself. Methods separating the evidentiary particle signal from background noise would enable a powerful new and widely applicable forensic capability. This capability would augment traditional footwear pattern evidence with objective quantitative associations, addressing one of the specific issues raised in the 2009 NAS report. Our prior NIJ research has shown corresponding particle sets to provide extremely strong, objective, quantitative, associative evidence. We hypothesize that by separately analyzing particles harvested from the outermost contact surfaces and the more protected recessed areas of footwear soles, we will be able to detect sequential footwear exposures and enable the widespread use of this new forensic capability.
The procedures used by crime scene officers have changed little in a hundred years; footwear evidence is still photographed and cast if deemed of importance. Footprints are the neglected ‘Cinderella’ evidence of the crime scene, especially as time pressures of CSI grows. We are addressing this by placing a simple tool for the 3D analysis of footwear evidence in the hands of every CSI officer. The research team at Bournemouth have fused computer and earth sciences to translate academic research on fossil footprints into freeware for use by police forces and forensic services across the UK.
This research will be conducted with the support of the University of Cambridge in conjunction with Julie Henderson completing her Master's study. It is the start of further work that she will be doing around the Tread Finder App that she developed and looking to the future. Ms. Henderson intends to complete her Ph.D. starting in September, through Huddersfield University, to examine the effectiveness of the crime scene capture device that Bo Li (Everspry) has produced with a view to measuring the ability of the digital crime scene image to be coded and compared remotely against the Tread Finder in-custody scan.
A software system, called SHOECALC, is being developed at NIST. It is designed to help both researchers and footwear examiners in the assessment of metrics or scoring procedures that provide objective characterizations of correspondences and discrepancies between features from two footwear impressions being compared.
The purpose of this project is develop statistically sound methods for matching shoe prints and appropriately quantifying the uncertainty in matching decisions. This research will focus on the problem of matching a crime scene impression to a particular shoe, as opposed to identifying the sizes, brands, or models of shoes consistent with a given print.
This Small Business Innovation Research Phase I project is aimed at developing a novel cost-effective 3D printing process to manufacture shoes. Currently shoes are mass manufactured, typically overseas, using fixed molds that do not optimally meet the need of an individual. 3D printing of shoes offers the promise of providing individual customization tailored not just to fit, style, and colors, but to individual biomechanics and medical needs, the latter of which are being poorly met with mass manufactured shoes.
There remains a significant research deficit concerning the spatial distribution of RACs on outsoles, of which existing published work cannot clarify. In response to this fundamental need for study, the aim of this project is to perform a detailed assessment of RAC distributions as a function of outsole contact area and tread design, using the largest currently available database of 72,306 acquired features collected from 1,300 outsoles.
Plenoptic cameras preserve directional information of oncoming light rays. Post-acquisition computation of images yield depth estimates (dimension) and enable scene reconstruction under different optical configurations (aperture, focus) from the actual acquisition.
Develop prototype software for detection of tread ridges in outsole imagery to facilitate the extraction and analysis of tread patterns. The method is now being adapted to better handle the specific shading patterns observed in outsole images and impressions which provide cues to 3D shape, in particular which components of the tread (e.g. ridges) are likely to leave behind impressions or prints.
The FBI Laboratory and the National Institute of Justice will establish a working group to evaluate the level-of-effort required to develop a more comprehensive footwear databaes that is available to state and local law enforcement agencies for use in their forensic casework. In addition, the FBI Laboratory may leverage the expertise of this working group to assist in the planning, development, and execution of footwear blackbox/white box research studies. Finally, the FBI Laboratory will assess the ability of conducting similar database development and/or research in other pattern-based disciplines.
Forensic footwear examination and interpretation is a complex and distributed activity influenced by a host of competing and evolving factors that vary as a function of case attributes and examiner experience. The aim of this project is to use the dominance-based rough set approach (DRSA) to better discern how examiners interpret the pattern recognition process of footwear comparison from start to finish.
The goal of this project is to calibrate the conclusions made by examiners in the forensic pattern disciplines and determine how expanded scales might be used by examiners. These expanded scales add precision to the determination made by examiners, but also may be misinterpreted by detectives, prosecutors, or the Court. In addition, definitive conclusions such as Identification have been interpreted by many members of the public to mean to the exclusion of all others, and many authors have suggested alternative language in the form of strength-of-evidence statements such as Strong Support for Common Source. The need to calibrate the language used for forensic conclusions was noted both by a subcommittee of the Organization of Scientific Area Committees (OSAC) and the National Research Council of the National Academies.