ICF-Body: A Multimodal Sensor Fusion Dataset for In-Cabin Estimation of Occupant Body Pose and Anthropometric Measurements

We introduce ICF-Body, a multimodal in-cabin sensor fusion dataset. Our dataset aims to allow the development and benchmarking of in-cabin sensor fusion algorithms for estimating (a) occupant body pose and (b) anthropometric measurements. Both tasks are closely related, as knowledge of body dimensions and proportions ensures a consistent body model across different poses. ICF -Body is the first dataset that contains temporal data from a memory seat configuration sensor (SCS) and a belt webbing extraction sensor (WES), in addition to near-infrared (NIR) images, RGB images, ultra-wideband (UWB), and 60 GHz radar. A time-of-flight (ToF) camera was used for dynamic body pose ground truth labeling, providing thirteen 3D keypoints. Seven body measurements were obtained as static anthropometric ground truth labels for each participant. The availability of accurate estimates of (a) body pose and (b) anthropometric measurements will be crucial for future restraint systems to allow the precise adaptation of deployment characteristics.