# 14 Lectures on Visual SLAM (slambook)

edition 2 of the slambook

Repository: https://github.com/gaoxiang12/slambook2
Canonical: https://ross.abutalabs.com/products/14-lectures-on-visual-slam-slambook
Language: C++
License: MIT
License Family: permissive
Last push: 2024-12-27T07:33:49+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2936, "days_push": 614, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 6656, forks 2181 (observed 2026-08-28T04:09:47.427831+00:00)

## What it is
Companion code repositories for the book '14 Lectures on Visual SLAM: From Theory to Practice', organized by chapter with C++ examples covering visual odometry, nonlinear optimization, loop closure, and dense reconstruction. Includes the original edition (slambook), the updated second edition (slambook2), and an English edition (slambook-en).

## Use cases
- learn visual SLAM from theory to practice
- example code for visual odometry with OpenCV
- learn g2o and Ceres pose graph optimization
- understand Lie groups and Lie algebra for robotics
- implement loop closure with DBoW3
- build dense 3D reconstruction with Octomap

## When to choose
- you are studying visual SLAM and want runnable chapter-by-chapter C++ examples
- you want a structured curriculum pairing a textbook with code
- you need reference implementations of VO, pose graph optimization, and bag-of-words loop closure

## When to avoid
- you need a production-ready SLAM system to deploy on a robot
- you want a maintained library rather than educational code
- you are not working in C++ on Linux

## Facets
- artifact type: learning-resource
- maturity: stable
- function: computer-vision, simulation, math, developer-tools
- domain: robotics, computer-vision, tutorials
- platform: cpp, cross-platform
- tags: slam, visual-odometry, eigen, g2o, ceres, book-code, education, algorithms, linux

## Member repositories
- gaoxiang12/slambook2 (main) score 32
- gaoxiang12/slambook (mirror) score 32
- gaoxiang12/slambook-en (docs) score 36

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:47.427831+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:37:35.580843+00:00, confidence not recorded.
  - readme: https://github.com/gaoxiang12/slambook2 (fetched 2026-08-28T04:09:47.427831+00:00, sha 5c7bf9deed4b)
- Data as of 2026-08-30T08:39:29.467469+00:00.