3D computer vision involves using algorithms and systems to interpret and understand three-dimensional structures from visual data like images or videos. It enables machines to analyze depth, shape, and spatial relationships in a scene. Applications range from object recognition to 3D scene reconstruction. A key aspect is depth estimation, which determines the distance of objects from the camera. Techniques include stereo vision, which uses two camera views, and depth sensors like LiDAR. These methods are essential for creating 3D models of environments in applications like robotics and augmented reality. Another critical use is motion analysis. By tracking objects in 3D space, systems like self-driving cars can make real-time decisions based on their surroundings. 3D computer vision also supports virtual reality by enabling realistic scene rendering and interaction.
What is 3D computer vision?

- Getting Started with Milvus
- Optimizing Your RAG Applications: Strategies and Methods
- AI & Machine Learning
- Information Retrieval 101
- Embedding 101
- All learn series →
Recommended AI Learn Series
VectorDB for GenAI Apps
Zilliz Cloud is a managed vector database perfect for building GenAI applications.
Try Zilliz Cloud for FreeKeep Reading
How do AI agents facilitate decision support systems?
AI agents play a significant role in enhancing decision support systems (DSS) by providing data analysis, predictive mod
What are the advantages of using a relational database?
Relational databases offer several significant advantages that make them a preferred choice for many development project
How is swarm intelligence used in energy management?
Swarm intelligence, which draws inspiration from the collective behavior of social organisms like ants, bees, or flocks