MistSeeker Vision
Image & Video Understanding Engine
MistSeeker Vision is an experimental perception architecture developed within Convia Labs.
Note: It is a research-oriented MVP, not a finished commercial product.
The project explores how image and video understanding can be made more interpretable, structured, and physics-aware at the perception stage.
MistSeeker Vision explicitly decomposes visual inputs into independent analytical modules—color, curvature, shadow, and text—and provides mathematical formulations for each. The system supports 2D, 3D, and time-dependent (4D) inputs and converts visual information into structured feature vectors suitable for multimodal LLM integration.
At its current stage, MistSeeker Vision serves as:
- •a well-defined architectural framework
- •a working open-source MVP
- •an educational and research baseline for structured perception
It is designed for experimentation, discussion, and future expansion into high-precision perception systems.
📄 Includes
- •Core perception pipeline (2D / 3D / 4D)
- •Physics-aware curvature & shadow models
- •Structured outputs for LLM integration
- •Examples and theory documentation
Note: This project is part of Convia Labs and is shared for research and educational purposes. APIs, interfaces, and internal designs may change as the project evolves.