# reacTIVision Amoeba > Source: https://docs.barcoder.ai/docs/standards/reactivision-amoeba > research date 2026-06-04 · extracted at 2026-10-03 > Publisher: Barcoder — encyclopedia of QR, barcode and payment-code standards Specifications: - [reacTIVision — official site](https://reactivision.sourceforge.net/) - [reacTIVision: A Computer-Vision Framework for Table-Based Tangible Interaction (TEI 2007)](https://modin.yuri.at/publications/reactivision_tei2007.pdf) ## Overview The **reacTIVision amoeba fiducial** is a **topological** marker — its identity is encoded not in a grid of bits but in the *nesting structure* of black and white blobs (its "amoeba" shape) [1][1], [2][2]. reacTIVision, the open-source computer-vision framework that reads these markers, tracks each marker's **ID, position and rotation** and streams them over the **TUIO** protocol; it was built as the sensing layer for tangible tabletop interfaces [1][1]. Unlike the pose-from-square fiducials [ArUco](https://docs.barcoder.ai/docs/standards/aruco) and [AprilTag](https://docs.barcoder.ai/docs/standards/apriltag), amoeba markers target flat tabletop tracking (2D position + orientation on a surface) rather than full 6-DoF camera pose, but they are the same class of robustly-detectable ID-carrying visual code. ## History reacTIVision was developed by **Martin Kaltenbrunner** and **Ross Bencina** at the Music Technology Group, Universitat Pompeu Fabra (Barcelona), as the underlying sensor component of the **Reactable** — a tangible modular synthesizer that set the standard for tangible multi-touch applications [1][1]. The amoeba fiducial design and its evolution were described in Bencina & Kaltenbrunner's work around 2005, and the framework was presented as *"reacTIVision: A Computer-Vision Framework for Table-Based Tangible Interaction"* at **TEI 2007** [2][2]. The project has been maintained for over a decade, with releases continuing into the 2020s [3][3]. ## Technical specification **Topological encoding.** Each amoeba fiducial is detected by building a **region adjacency tree** (the topological tree of nested black and white regions) from the thresholded image; the unique sequence of region nesting encodes the marker's ID, while the centroids of the leaf regions give position and 2D orientation [1][1], [2][2]. Because identity is purely topological, detection is robust and the markers can be made small and irregularly shaped — the characteristic "amoeba" look results from a **genetic / evolutionary algorithm** that searched for compact shapes satisfying the required tree structures [1][1]. **Fiducial sets.** The default **"amoeba"** set contains **216 distinct symbols** (`symbols/default.pdf`) [1][1], [3][3]. The framework also ships other sets and a beta **"yamaarashi"** set able to distinguish **over one million** different markers in a more compact footprint [3][3]. Multi-touch finger tracking (detecting round white regions as fingertips) is also supported but off by default [3][3]. **Output / TUIO.** reacTIVision transmits results using the **TUIO** protocol as **Open Sound Control (OSC) messages over UDP** (default port **3333** to localhost) [1][1], [3][3]. TUIO assigns a per-object **session ID** alongside the fiducial ID, so clients can track object lifetimes [1][1]. ## Use cases - **Tangible user interfaces** — the canonical use; physical objects on a table become controllable tokens [1][1]. - **The Reactable** — tangible modular music synthesizer driven entirely by amoeba-tagged pucks [1][1]. - **Multi-touch interactive surfaces** — finger tracking on tabletop displays [3][3]. - **Rapid TUI prototyping** — its design goal as a toolkit [1][1]. ## Implementations - **`mkalten/reacTIVision`** — C; the official cross-platform (Windows, macOS, Linux) framework, GPL v2+; includes the amoeba and yamaarashi symbol sets and TUIO output (~322 stars, active 2026) [3][3]. TUIO client libraries are LGPL, allowing use in proprietary clients [1][1]. ## Comparison Versus [ArUco](https://docs.barcoder.ai/docs/standards/aruco) and [AprilTag](https://docs.barcoder.ai/docs/standards/apriltag): those are **bit-grid** square fiducials decoded by reading cells and recovering full 6-DoF camera pose; amoeba fiducials are **topological** (decoded from the region-nesting tree) and are aimed at **2D tabletop** position/orientation streamed via TUIO rather than 6-DoF pose [1][1], [2][2]. The topological approach tolerates irregular, brand-friendly shapes and small sizes, and the yamaarashi set's >1M ID capacity rivals the large ID spaces of [TopoTag](https://docs.barcoder.ai/docs/standards/topotag); the trade-off is reliance on a controlled, near-planar tabletop imaging setup. It shares the topological-decoding idea later generalized by [TopoTag](https://docs.barcoder.ai/docs/standards/topotag). ## Fun facts - The "amoeba" shapes were not hand-drawn — they were **evolved by a genetic algorithm** to minimize marker size while keeping the required topology [1][1]. - The whole framework exists because of a musical instrument: the **Reactable** [1][1]. ## Status **Active, mature open source.** reacTIVision remains maintained (repository active into 2026) and TUIO is a widely adopted standard for tangible/tabletop interaction [3][3]. ## Sources [1]: https://reactivision.sourceforge.net/ [2]: https://modin.yuri.at/publications/reactivision_tei2007.pdf [3]: https://github.com/mkalten/reacTIVision/blob/master/README.md 1. [reacTIVision (official site)][1] — Kaltenbrunner & Bencina, accessed 2026 2. [reacTIVision: A Computer-Vision Framework for Table-Based Tangible Interaction][2] — Kaltenbrunner & Bencina, TEI, 2007 3. [reacTIVision README][3] — mkalten/reacTIVision, GitHub, accessed 2026 ## Deployments _No country reports mention this standard by name._ ## Regions / aggregations not mapped to a single country - Universal