Footwear impressions are commonly found at crime scenes and are therefore a valuable source of evidence for criminal investigations. Forensic experts can show that a footwear impression was made by a specific shoe or impressions at different crime scenes were made by the same suspect by comparing individual characteristics of the impressions. However, this process is very time consuming, therefore automated solutions are desired. Yet, testing and training such methods requires datasets that on the one hand reflect real data from criminal cases and on the other hand provide ground truth information. To solve this, we created an acquisition line and captured footwear impressions of 300 different pairs of shoes under varying conditions with the help of the Austrian police. In this work the creation of this dataset and the dataset itself is described in detail.
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