Relative Camera

Relative camera pose estimation focuses on determining the spatial relationship (rotation and translation) between two or more camera viewpoints, a crucial task in various computer vision applications. Current research emphasizes developing robust and accurate methods, exploring both traditional geometry-based approaches (e.g., using feature correspondences and geometric constraints) and deep learning models (e.g., transformer networks, convolutional neural networks) that directly predict relative poses, often incorporating object detection or scene context for improved performance. These advancements have significant implications for applications such as augmented reality, autonomous navigation, 3D reconstruction, and large-scale scene understanding, enabling more accurate and reliable scene modeling and object localization.