Also, considering the nature of this project (built in the Unity Engine), the code files seen on this repository only reflect the backend code implementation, not the visuals, 3D rendering, or other such aspects of the project.
Viseon is a 3D spatial entertainment discovery platform built in Unity. Users navigate through a large interactive world made up of five interconnected biomes: cliffs, forests, caves, oceans, and mountains. Each biome is mapped to a distinct genre: horror, drama, mystery, sci-fi, and action respectively. With room for more. Importantly, these genre zones are not discrete. As users move through the world, we calculate continuous proximity scores to each biome, forming a dynamic genre distribution at any location. These distributions directly influence content suggestions.
As users explore, translucent Media Orbs appear in the environment. Each orb contains a movie tailored to the current genre distribution based on the player’s spatial position. The orb is not static. It is generated live by querying a backend content selection model that takes in the genre proximity vector and returns a single film that best represents that blend. For example, standing between forest and cave might yield a mystery-drama recommendation. The orbs are fully interactive—clicking one spawns a display that shows additional metadata or content (e.g. poster, trailer, description).
Beyond the physical world, there’s a recommendation zone placed in the sky above the environment. This is the “Your Recommendations” section, where five personalized Media Orbs are spawned based on long-term preferences. These are not influenced by spatial location. Instead, the user is assigned a vector representation encoding hypothetical past preferences, and a cloud-based content selection service returns the top five matches based on learned similarity. These five results are rendered in real time in the sky and can be interacted with just like the local orbs on the ground.
Viseon isn’t just visually engaging. It’s a hybrid system combining environment-driven discovery, continuous proximity logic, ML-style personalized inference, and backend model-based generation, all running together in an explorable, real-time space.
The world was created using Unity’s terrain system, custom lighting, and shader effects. Each biome has a defined spatial region with continuous gradient blending at the borders. Using the player’s world coordinates, we compute distances to each biome center and normalize them into a five-dimensional proximity vector. This represents the user’s current “genre weighting” at any given location.
When a new Media Orb is triggered, a request is sent to a hosted backend model which interprets the genre distribution and returns a movie that best represents that specific mix. The model uses internally indexed genre embeddings and simple vector similarity to pick representative titles. These titles are curated and return only a single result to maximize clarity and precision in the spatial world.
Each orb is instantiated with a movie title, attached metadata, and a stylized semi-transparent display screen that opens when the user clicks on it.
The “Your Recommendations” system is powered by a ML cloud function, which simulates a personalized recommendation engine. The system assigns a sample user ID, queries the function, and retrieves five recommendations based on vector similarity to learned preferences. These results are mapped to GameObjects floating above the world and update at load time.
Unity handles rendering, object pooling, and logic. We use asynchronous HTTP requests to interact with the cloud endpoints and parse results for in-game use. The entire system is modular, allowing genre count, biome mappings, and content sources to be changed independently of the world structure.