First-Person Perspective
The CSV data files in the ZIP archive are analytical datasets extracted and processed from the RUG-EGO-FALL dataset, intended to support fall detection research using wearable first-person perspective devices. The data includes visual motion information for each video frame, calculated using the ORB (Oriented FAST and Rotated BRIEF) feature point algorithm in combination with the Lucas-Kanade optical flow method.
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This dataset aims to support research on temporal segmentation of the Timed Up and Go (TUG) test using a first-person wearable camera. The data collection includes a training set of 8 participants and a test set of 60 participants. Among the 8 participants, the test was completed at both a normal walking pace and a simulated slower walking pace to mimic elderly movement patterns. The 60 participants were randomly divided into two groups: one group completed the test at a normal walking pace, and the other group simulated slower walking speed to mimic elderly movement patterns.
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