Forensic interpretation framework for body and gait analysis: feature extraction, frequency and distinctiveness

Surveillance is ubiquitous in modern society, allowing continuous monitoring of areas that results in capturing criminal (or suspicious) activity as footage. This type of trace is usually examined, assessed and evaluated by a forensic examiner to ultimately help the court make inferences about who was on the footage. The purpose of this study was to develop an analytical model that ensures applicability of morphometric (both anthropometric and morphological) techniques for photo-comparative analyses of body and gait of individuals in CCTV images, and then to assign a likelihood ratio. This is the first paper of a series: This paper will contain feature extraction to observe repeatability procedures from a single observer, in turn, producing the frequency and distinctiveness of the feature set within the given population. To achieve this, an Australian population database of 383 subjects (stance) and 268 subjects (gait) from both sexes, all ages above 18 and ancestries was generated. Features were extracted, defined, and their rarity viewed among the developed database. Repeatability studies were completed in which stance and gait (static and dynamic) features contained low levels of repeatability error (0.2%–1.5 TEM%). For morphological examination, finger flexion and feet placement were observed to have high observer performance.