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How the Processing Mode Influences Azure Kinect Body Tracking Results.
| Content Provider | Europe PMC |
|---|---|
| Author | Büker, Linda Quinten, Vincent Hackbarth, Michel Hellmers, Sandra Diekmann, Rebecca Hein, Andreas |
| Editor | Munteanu, Adrian |
| Copyright Year | 2023 |
| Abstract | The Azure Kinect DK is an RGB-D-camera popular in research and studies with humans. For good scientific practice, it is relevant that Azure Kinect yields consistent and reproducible results. We noticed the yielded results were inconsistent. Therefore, we examined 100 body tracking runs per processing mode provided by the Azure Kinect Body Tracking SDK on two different computers using a prerecorded video. We compared those runs with respect to spatiotemporal progression (spatial distribution of joint positions per processing mode and run), derived parameters (bone length), and differences between the computers. We found a previously undocumented converging behavior of joint positions at the start of the body tracking. Euclidean distances of joint positions varied clinically relevantly with up to 87 mm between runs for CUDA and TensorRT; CPU and DirectML had no differences on the same computer. Additionally, we found noticeable differences between two computers. Therefore, we recommend choosing the processing mode carefully, reporting the processing mode, and performing all analyses on the same computer to ensure reproducible results when using Azure Kinect and its body tracking in research. Consequently, results from previous studies with Azure Kinect should be reevaluated, and until then, their findings should be interpreted with caution. |
| Journal | Sensors (Basel, Switzerland) |
| Volume Number | 23 |
| DOI | 10.3390/s23020878 |
| PubMed Central reference number | PMC9860777 |
| Issue Number | 2 |
| PubMed reference number | 36679675 |
| e-ISSN | 14248220 |
| Language | English |
| Publisher | Molecular Diversity Preservation International (MDPI) |
| Publisher Date | 2023-01-12 |
| Access Restriction | Open |
| Subject Keyword | Azure Kinect body tracking skeleton tracking Azure Kinect Body Tracking SDK reproducibility quality assurance |
| Content Type | Text |
| Resource Type | Article |
| Subject | Biochemistry Instrumentation Information Systems Medicine Analytical Chemistry Atomic and Molecular Physics, and Optics Electrical and Electronic Engineering |