In current forensic practice, there are few standards for outdoor crime scene documentation, despite the need for such documentation to be accurate and precise in order to preserve evidence. A potential solution to this is the implementation of image-based photogrammetry. Applied Structure from Motion (SfM) reconstructs models through image point comparisons. A 3D model is produced from a reference photoset that captures a 360-degree view of the subject and the software employs triangulation to match specific points, datums, across individual photos. The datums are arranged into a point-cloud that is then transformed into the final model. Modifying the point-cloud into a final product requires algorithms that adjust the points by building a textured mesh from them. One of the disadvantages of SfM is that the point-cloud can be “noisy,” meaning that the program is unable to distinguish the features of one datum from another due to similarities, creating coverage gaps within the meshed images. To compensate for this, the software can smooth portions of the model in a best-guess process during meshing. As commercial software does not disclose the adjustment algorithms, this documentation technique, while very useful in other disciplines that regularly apply SfM such as archaeology, would fail to meet the standards of the Daubert and Kumho criteria in a forensic setting.
A potential solution to this problem is to use open-source software, which discloses the adjustment algorithms to the user. It was hypothesized that the output of open-sourced software solutions would as accurate as the models produced with commercial software and with total station mapping techniques. To evaluate this hypothesis, a series of mock outdoor crime scenes were documented using SfM and traditional mapping techniques. The scenes included larger surface scatter and small surface scatter scenes. The large surface scatter scenes contained a dispersed set of plastic human remains, and various objects that might reasonably be associated with a crime scene. Ten of these scenes were laid out in 10 x 10 m units in a New England forested environment, each grid with a slightly different composition, and then documented using an electronic total station, data logger and digital camera. The small surface scatter scenes consisted of a pig mandible placed in different environments across two days of data collection. The resulting models were built using PhotoScan by AgiSoft, the commercial software, and MicMac for Mac OSX as the open-source comparison software. Accuracy is only part of the concern however; the full utility of any one of the workflows is defined additionally by the overall cost-effectiveness (affordability and accessibility) and the visual quality of the final model. Accuracy was measured by the amount of variance in fixed-datum measurements that remained consistent across scenes, whereas visual quality of the photogrammetric models were determined by cloud comparison histograms, which allows for comparison of models between software types and across different days of data collection. Histograms were generated using CloudCompare. Not all models that were rendered were useable—90% of large surface scatter models and 87.5% of small surface scatter models were useable.
While there was variance in the metric outputs between the total station and photogrammetric models, the average total variance in fixed-datum lengths for individual scenes was below 0.635 cm for six of the ten scenes. However, only one of the large surface scatter scenes produced measurement that were significantly different between the total station measurements and the software measurement. The maximum differences in measurement between the total station and software measurements were 0.0917 m (PhotoScan) and 0.178 m (MicMac). The minimum difference that was found for either software was 0.000 m, indicating exact measurement. The histograms for the large scatter scenes were comparable, with the commercial and open-source software-derived models having low standard deviations and mean distances between points. For the small surface scatter scenes, the histograms between software types varied depending on the environment and the lighting conditions on the day of data collection. Conditions such as light, ground foliage and topography affect model quality significantly, as well as the amount of available computing power. No such issues of losing objects or limitations of computing power were encountered when mapping by total station and processing the data in AutoCAD. This research shows that SfM has the potential to be a rapid, accurate and low-cost resource for forensic investigation. SfM methodology for outdoor crime scene documentation can be adapted to fit within evidentiary criteria through the use of open-source software and transparent processing, but there are limitations that must be taken into consideration.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/38598 |
| Date | 09 October 2019 |
| Creators | Church, Elizabeth |
| Contributors | Pokines, James T. |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
| Rights | Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
Page generated in 0.0024 seconds