Active Stereo Camera

Active stereo cameras aim to create accurate 3D models by combining images from two slightly offset viewpoints, overcoming limitations of single-camera depth sensing. Current research focuses on improving depth map accuracy, particularly for challenging objects like transparent materials and highly reflective surfaces, often employing deep learning techniques such as stereo networks and integrating them with algorithms like YOLO for object detection and segmentation. These advancements are driving progress in robotics (e.g., grasping), agriculture (e.g., automated pruning), and other fields requiring precise 3D scene understanding, particularly where robust and accurate depth information is crucial.