Occupancy Information

Occupancy information, encompassing the detection and prediction of object presence and movement within a space, is crucial for various applications, particularly autonomous driving and building energy management. Current research focuses on developing robust and efficient methods for occupancy estimation using diverse data sources (LiDAR, cameras, CO2 sensors) and model architectures, including transformers, convolutional neural networks, and point-based representations, often incorporating information fusion techniques. These advancements improve the accuracy and real-time capabilities of occupancy prediction, leading to safer autonomous navigation, optimized energy consumption in buildings, and enhanced understanding of human-environment interaction.