The field of human motion tracking and localization is rapidly advancing, with a focus on developing scalable and accurate methods for capturing human motion data in large and complex environments. Researchers are exploring the use of novel technologies such as Ultra-Wideband (UWB) localization, which offers a promising alternative to traditional vision-based systems. Noteworthy papers include: Collecting Human Motion Data in Large and Occlusion-Prone Environments using Ultra-Wideband Localization, which investigates the use of UWB for human motion capture in crowded environments. Adaptive Robot Localization with Ultra-wideband Novelty Detection, which proposes a robust and adaptive UWB localization method for indoor confined spaces. TPT-Bench: A Large-Scale, Long-Term and Robot-Egocentric Dataset for Benchmarking Target Person Tracking, which introduces a large-scale dataset for target person tracking in crowded and unstructured environments. Robust Indoor Localization via Conformal Methods and Variational Bayesian Adaptive Filtering, which proposes a hierarchical robust framework for indoor localization. OptiGait-LGBM: An Efficient Approach of Gait-based Person Re-identification in Non-Overlapping Regions, which proposes an efficient approach for gait-based person re-identification in non-overlapping regions.