CVMay 21, 2025

A Taxonomy of Structure from Motion Methods

arXiv:2505.15814v12 citationsh-index: 1
Originality Synthesis-oriented
AI Analysis

This is an incremental conceptual review that organizes existing SfM approaches for researchers in computer vision.

The paper tackles the problem of categorizing Structure from Motion (SfM) methods, proposing a taxonomy that groups them into three main categories based on their focus on motion or structure, and provides insights into theoretical conditions and open problems.

Structure from Motion (SfM) refers to the problem of recovering both structure (i.e., 3D coordinates of points in the scene) and motion (i.e., camera matrices) starting from point correspondences in multiple images. It has attracted significant attention over the years, counting practical reconstruction pipelines as well as theoretical results. This paper is conceived as a conceptual review of SfM methods, which are grouped into three main categories, according to which part of the problem - between motion and structure - they focus on. The proposed taxonomy brings a new perspective on existing SfM approaches as well as insights into open problems and possible future research directions. Particular emphasis is given on identifying the theoretical conditions that make SfM well posed, which depend on the problem formulation that is being considered.

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