3D Object Reconstruction from Images: Investigating techniques for 3D object reconstruction from images, including structure-from-motion and multi-view stereo algorithms
Keywords:
Photogrammetry, 3D ModelingAbstract
3D object reconstruction from images is a fundamental problem in computer vision with applications in augmented reality, robotics, and cultural heritage preservation. This paper presents a comprehensive review of techniques for 3D object reconstruction from images, focusing on structure-from-motion (SfM) and multi-view stereo (MVS) algorithms. SfM algorithms aim to recover the 3D structure of a scene from a set of 2D images, while MVS algorithms reconstruct the geometry of objects by combining information from multiple views. We discuss the principles behind these algorithms, their advantages and limitations, and current research trends. Additionally, we explore the challenges and future directions in 3D object reconstruction, such as dealing with large-scale scenes, handling occlusions, and improving reconstruction accuracy. This paper provides a valuable resource for researchers and practitioners interested in 3D reconstruction from images.
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