Inter-observer variation of head and foot point selection for subject height determination

The purpose of this study was to examine factors affecting video analysts' decisions in marking the vertex of the head and foot point and corresponding inter-observer marking variances when conducting height analysis on individuals seen in video. Nineteen video analysts participated in an exercise at the 2022 Ontario Forensic Video Analysts' Association (OFVAA) conference where they were asked to mark the vertex of the head and a corresponding foot point of a "suspect" on extracted video frames in a variety of positions and with different headwear (no headwear, baseball cap, and hoodie). A height scale with discrete marking points located at the same positions as where the suspect was positioned was also included in a separate image set, offering a comparison to the suspect. Marked points for all analysts were overlayed onto the respective image frame for visual observations. Summary statistics were used for data interpretation. This study demonstrated that factors such as the suspect's proximity to the camera and suspect's headwear affected the variability and range of marking, which has a direct correlation to the estimated height of the suspect. In general, when the region to be marked was larger, the variability was also larger. This study also demonstrates that marking errors were significantly reduced when discrete marking locations were present such as on a height scale. The average percentage difference of height was most notable, approximately 3%, when the suspect was wearing a hoodie and was at a position closest to the camera. The range of the percentage difference was also the highest at this position, which was 10.6%. In comparison, the height scale had a maximum percent height difference of 0.6% at position D-5, the furthest position from the camera. The range at this location was approximately 2%, which was also the highest range value for the height scale. Future studies should consider suspect posture and look at how these errors may be minimized by examining the best locations to mark the head and foot points under different scenarios.