Table and Figure Caption List

Table 1. Demographic Characteristics of Participants in the Combined Dataset (Controlled-Setting and Real-world), Controlled-Setting Position Dataset, and Real-world Dataset
Table 2. Total Number of Annotations Containing Each Class in the Real-world Dataset, Controlled-Setting Dataset, and Combined (Controlled-Setting and Real-world) Dataset on Which SLeeP AIDePt-2 was Trained
Figure 1. Bar Chart of the Frequency of Occurrences of Each Sleeping Position Class and the Sitting Class in the Real-world Dataset and Controlled-Setting Dataset. Legend : Real-world dataset shown in blue, and controlled-setting dataset shown in orange.
Figure 2A. Bar Chart of SLeeP AIDePt-2 Performance Metrics From the Testing Phase Averaged Across the Five Models’ Test Sets and Across All Classes. Legend : mAP@0.50 indicates the mean average precision at an intersection of union of 0.50. mAP@.50-.95 indicates the mean average precision at intersections of unions between 0.50 and 0.95. The error bars represent one standard deviation of the respective value across all measures, which reflects the variability both across models and classes. The y-axis does not have units because precision, recall, mAP@0.50, and mAP@.50-.95 are dimensionless values.
Figure 2B. Heatmap of SLeeP AIDePt-2 Performance Metrics (Columns) From the Testing Phase Averaged Across the Five Models’ Test Sets For Each of the Predicted Classes (Rows). Legend : AP@0.50 indicates the average precision at an intersection of union of 0.50. AP@.50-.95 indicates the average precision at intersections of unions between 0.50 and 0.95. The value of the respective performance metric is mapped to a colour spectrum from red to yellow to green where values of 0.50 or less are represented by red at the lower end of the spectrum, values around 0.75 are shades around yellow (oranger if lower than 0.75; greener if higher than 0.75), and values of 0.90 or more are represented by green at the higher end of the spectrum. The “all body position classes average” is provided as the averaged value of the respective performance metric across the five models’ test sets and the 13 body position classes. For the “all body position classes average” row, the value in the AP@0.50 column is the mean AP@0.50, and the value in the AP@.50-.95 column is the mean AP@.50-.95 since these values represent averages across multiple classes.
Figure 3. Example Output of SLeeP AIDePt-2 Localising and Classifying the Sleeping Positions of a Study Participant and Their Bed Partner as Well as Their Pillows in Eight Different Extracted Frames.Legend : The participant’s and bed partner’s body and pillow annotations are shown by the coloured boxes (“Ground Truth”, left). The model’s localization and prediction of the sleeping positions and pillows, along with its confidence score (between 0 and 1) at the top of each bounding box, are shown (“Prediction”, right).