Heimdall Vision

Heimdall Vision is a community project that develops an open-source object-detection model specifically for CCTV and surveillance footage. Users can install the trained model on their own camera setups and contribute images and labels to help retrain it. The project pools contributions from many independent users to address the limited range of conditions any single camera setup can capture.

The process works in four steps: first, install the current trained model on your own camera setup; second, upload images when the model makes a miss or low-confidence detection; third, annotate by labeling what the model got wrong or missed; and fourth, the shared model is retrained on everyone's contributions at regular intervals. This cycle ensures the model improves over time based on real-world usage.

The project is designed for anyone with a CCTV or surveillance camera setup who wants to improve object detection accuracy. It suits users who need a shared, open model that benefits from diverse global conditions, such as different climates, angles, and lighting scenarios. Users can either contribute their own footage to train the model or simply use the trained model for free without contributing.

To get started, users can sign in to the website to either contribute their own camera images and labels or just use the trained model. Both options are completely free, and there is no cost to install or run the model on personal camera setups. Signing in allows users to begin contributing footage or utilizing the shared model immediately.

The project relies on diversity rather than raw volume to improve the model. Night footage, rain, snow, IR/thermal cameras, and unusual angles are specifically highlighted as conditions that make the community model meaningfully stronger. A thousand more daytime images of the same suburban driveway teach the model very little it doesn't already know.

Uploaded images are never visible to other users, ensuring privacy for contributors. Only the contributor and admins reviewing new contributors before they are trusted can see the images. This structure protects user data while allowing the community to build a robust shared model.

Users grant Heimdall a license to store, process, and use their uploaded footage to train the one shared community model. This license allows the project to utilize the contributions for the specific goal of improving CCTV and surveillance footage detection. The project currently focuses on a single type of footage rather than offering multiple separate options.

Users are responsible for having a lawful basis to capture and share whatever they upload. This includes giving notice to and obtaining consent from anyone identifiable in the footage, such as passersby or license plates, where local law requires it. Users should not upload footage they do not have the right to share.

Users can delete their own images at any time if they wish to stop contributing. If someone else uploads footage that pictures the user and they want it removed, they can contact the team. Users can also request to know what data is held about them by reaching out directly.

Some users on Reddit mention that the name 'Heimdall' is associated with having vision, which aligns with the project's focus on object detection. While this is an opinion from a single user, it reflects a thematic connection to the project's name and purpose. The project itself does not explicitly state this connection in its official materials.

The official website provides a contact email for questions, data access, or removal requests. Users can reach out to the team via this email address to discuss any issues or requests related to their data or contributions. This is the primary method for direct communication provided in the public materials.

The project emphasizes that the hard part of building a surveillance AI is overcoming the narrow slice of the world seen by any single camera setup. A model trained only on one country, one climate, or a handful of angles will confidently misread anything it hasn't seen before. Thousands of independent contributors are needed to close this gap effectively.

The website states that the project is focused on building the world's best open-source surveillance AI through community collaboration. It explicitly claims that the best surveillance AI will never come from one company or one dataset alone. This is a marketing claim presented on the official site regarding the project's ultimate goal.

Heimdall Vision has no reviews on Trustburn yet. Anyone who has used it can write the first review on its Trustburn page.