Pistorius, ElenaRichter, SabineLabudde, DirkKlein, MaikeKrupka, DanielWinter, CorneliaWohlgemuth, Volker2023-11-292023-11-292023978-3-88579-731-9https://dl.gi.de/handle/20.500.12116/43195New methods for identifying individuals based on their digital skeleton (rig) gain attention in digital forensics. To ensure a solid comparison, understanding the development of this digital skeleton is crucial. One approach is manually creating a rig using a parametrized 3D room and cameras with embedded pictures, capturing multiple angles of the same person with markers on defined spots. Using these pictures and the room, a movable marker-based rig can be built in software like Blender (https://www.blender.org). It can be used to fit the rigged doll into another scene or compare proportions. For a similar process, algorithm-based software like OpenPose (https://github.com/CMU- Perceptual-Computing-Lab/openpose) estimates a digital skeleton from pictures or videos. The output includes JSON files with joint coordinates and pictures with embedded skeletons, which can manually be processsed into a rig. While these procedure can save time and expand applications, precision and supervision differ from marker-based rigs. A comparative study assessing similarity is discussed in the following paper.envideo analysiscomparisonindividual rigsText/Conference Paper10.18420/inf2023_721617-5468