Epipolar Plane Image

Epipolar Plane Images (EPIs) represent a powerful tool for processing multi-view imagery, particularly in 3D reconstruction and light field analysis. Current research focuses on improving EPI-based methods for tasks like depth estimation and stereo matching, often employing deep learning architectures such as convolutional neural networks and generative adversarial networks (GANs) to enhance accuracy and efficiency. These advancements are driving progress in various applications, including satellite imagery analysis, light field imaging, and omnidirectional computer vision, by enabling more robust and accurate 3D scene understanding from multiple viewpoints. The development of novel algorithms that leverage the inherent structure of EPIs, such as stitching techniques and self-supervised learning approaches, is a key theme in ongoing research.