Video & Motion

OpenPose

Real-time multi-person keypoint detection library for body, face, hands, and foot estimation.

Status
UnmaintainedNo commits in 753 days.
Last checked
Checked · Oct 10, 2026
License
Open source
Pricing
Free tier · from $0

What it is

OpenPose is a real-time multi-person keypoint detection library that estimates the location of human keypoints in images or video streams. It supports body, face, hand, and foot tracking, making it valuable for applications like motion capture, augmented reality, and health monitoring systems.

OpenPose stands out for its comprehensive support of body, face, hand, and foot tracking in real-time, making it a robust choice for applications requiring detailed human pose estimation.

When it fits — and when it doesn’t

A good fit for

  • Developers building real-time motion tracking systems who need high accuracy and multi-person support.

  • Researchers working on human-computer interaction projects requiring detailed body part detection.

Look elsewhere if

  • Projects with strict latency requirements where every millisecond counts, as OpenPose may introduce some processing delay.

  • Applications that require extremely lightweight solutions due to its computational demands.

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

  1. 01

    Steep learning curve for non-C++ developers

    The primary language is C++, which may be unfamiliar to many modern software engineers who primarily work with higher-level languages like Python or JavaScript.

  2. 02

    Resource-intensive, especially on low-end hardware

    Real-time processing of video streams requires significant computational resources, leading to potential performance issues on less powerful devices.

  3. 03

    Limited support for mobile platforms

    Optimized builds and documentation are primarily focused on desktop environments, making deployment on mobile devices challenging without substantial effort.

  4. 04

    Complex setup process

    Installation requires configuring multiple dependencies and setting up the environment correctly, which can be error-prone for users unfamiliar with C++ development.

  5. 05

    Sparse community support compared to more mainstream libraries

    While open-source, OpenPose has a relatively smaller user base and developer community, leading to fewer resources like tutorials, forums, and third-party integrations.

What it does well

  • Real-time multi-person keypoint detection

  • Support for body, face, hand, and foot tracking

  • High accuracy in various lighting conditions

  • Modular design allows customization

Pricing

Free tier
YesOpen source — free to use
Paid from
$0
Model
Flat rate
Enterprise plan
No

Pricing not independently confirmed — check the vendor’s page.

Performance benchmarks

How Fast Is It?

Set up OpenPose

Setup steps, common gotchas and what to check after 30 days.

Open the setup guide →
Get the badge

A small badge for OpenPose’s README or site: its name, “Tracked on AI Navigator”, and the availability status and check month from this page. It updates as the catalog does.

OpenPose — tracked on AI Navigator

Markdown

[![OpenPose — tracked on AI Navigator](https://navigateaitools.com/badge/openpose.svg)](https://navigateaitools.com/explorer/tool/openpose)

HTML

<a href="https://navigateaitools.com/explorer/tool/openpose"><img src="https://navigateaitools.com/badge/openpose.svg" alt="OpenPose — tracked on AI Navigator" height="58"></a>