Viewpoint Estimator

Viewpoint estimation aims to determine the camera's position and orientation relative to a 3D object from a single image or a sequence of images. Current research focuses on developing robust methods, particularly using neural radiance fields (NeRFs) and incorporating techniques like extended Kalman filters to improve accuracy and handle challenging scenarios such as significant camera movement and noisy data. These advancements are crucial for applications requiring 3D scene understanding, such as robotics, augmented reality, and computer vision tasks involving object reconstruction and manipulation. The field is actively exploring both data-driven deep learning approaches and more traditional model-based methods to achieve reliable and efficient viewpoint estimation.