Active Camera

Active camera systems dynamically adjust camera position and parameters to optimize visual data acquisition, addressing limitations of static camera setups. Current research focuses on using reinforcement learning, often incorporating multi-agent approaches and reward functions designed to encourage efficient exploration and occlusion avoidance, to control camera movement for tasks like 3D pose estimation, multi-object navigation, and non-line-of-sight imaging. These advancements are improving robotic perception, enabling more robust and efficient solutions in diverse applications such as autonomous navigation, surveillance, and remote sensing. The development of effective active camera control algorithms is crucial for enhancing the capabilities of autonomous systems and expanding the possibilities of computer vision.