Monocular Localization

Monocular localization aims to determine a camera's position and orientation using only a single image and a pre-existing map, a crucial task for robotics and autonomous systems seeking cost-effective solutions. Current research emphasizes robust methods that leverage semantic information (e.g., lane lines, buildings) rather than relying solely on texture features, often incorporating deep learning for feature extraction and pose estimation, and employing techniques like graph optimization to fuse data from multiple sources. This field is vital for advancing autonomous navigation, particularly in applications where GPS is unreliable or unavailable, and for improving the efficiency and accuracy of various computer vision tasks.