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Bloodstain pattern analysis plays a crucial role in forensic investigations. Projected patterns can offer valuable insights into the dynamics of crime scenes. In this paper, we propose and validate a novel approach that extends existing software, HemoVision, to analyze impact patterns that are distributed across multiple arbitrarily oriented surfaces. The proposed method integrates HemoVision’s marker-based system with structure from motion (SfM) techniques to reconstruct the three-dimensional geometry of impact patterns using only two-dimensional photographs. Controlled experiments were used to validate the proposed approach, demonstrating robustness in reconstruction accuracy with median translation errors below 3 mm and median angular errors below 0.2°, irrespective of imaging device or image resolution. Comparing the estimated areas origin to their known ground truth, the proposed method achieved an average total error of 8.12 cm, with the primary source of error being the vertical dimension. Despite this, the overall error remains well within the ranges of error reported in prior work. This study demonstrates that HemoVision can be used to analyze complex impact patterns using only two-dimensional photographs, providing forensic experts with an efficient and accessible tool for investigating intricate crime scenes involving multi-surface impact patterns. •HemoVision is extended with photogrammetry to create 3D scenes from 2D photographs.•Impact patterns were created in controlled experiments for validation.•3D reconstructions had median translation and rotation errors of 3 mm and 0.18°.•Resulting area of origin estimates had a mean total error of 8.12 cm.•HemoVision is an efficient and accurate tool for analyzing complex impact patterns.

•HemoVision is software that automates bloodstain impact pattern analysis.•Has not been validated and uses tangent method, which is known to be biased.•Propose method that formulates Area of Origin estimation as optimisation problem.•Present results from validation study using controlled experiments.•Proposed method significantly outperforms others and is significantly more robust. [Display omitted] Bloodstain impact pattern Area of Origin (AO) estimation is an important but time-consuming process in criminal investigations. HemoVision is a software package that automates and accelerates this process. To date, however, no study has been published that evaluates HemoVision’s accuracy. Moreover, HemoVision relies on an automated variant of the tangent method to estimate a pattern’s AO, even though the use of front-view projections has been shown to provide biased AO estimates. Therefore, the goal of this paper is twofold. First, a novel AO estimation method is proposed, whereby AO estimation is formulated as a least-squares optimisation problem that operates in three dimensions directly, eliminating the need for front view projections. Second, ten impact patterns with known AO coordinates at both 50 cm and 100 cm with respect to the target wall are created and used to compare the proposed approach’s accuracy and robustness to the manual tangent method, HemoSpat, and HemoVision’s automated tangent method. Results show that for impacts at 100 cm or less to the target wall, the proposed approach achieves the lowest average error of 17.29 cm with the least uncertainty, and that it performs significantly better than the manual tangent and automated tangent methods at a 5% significance level. Moreover, it is shown to achieve errors of less than 30 cm at these distances with just nine stains, whereas the automated tangent method requires a minimum of 16 stains to achieve the same average error.