Stereo vision is a computer vision technique that uses two or more cameras to capture images of the same scene from different viewpoints. By comparing these images, a computer can estimate the distance of objects and perceive depth, similar to how human eyes work.
The process involves finding matching points in both images and measuring their positional differences, known as disparity. These differences are then used to calculate how far objects are from the cameras.
How Are Depth Maps Generated?
A depth map is created by:
- Capturing images from multiple cameras.
- Identifying corresponding points in each image.
- Calculating the disparity between matching points.
- Converting disparity values into depth information.
The resulting depth map shows the distance of objects within the scene, where different pixel values represent different depths.
Applications of Stereo Vision
- Robotics: Navigation, obstacle detection, and object manipulation.
- Autonomous Vehicles: Depth perception, lane detection, and collision avoidance.
- 3D Reconstruction: Creating 3D models of objects, buildings, and environments.
- Drones: Terrain mapping and autonomous flight.
- Medical Imaging: Assisting in surgical visualization and analysis.
Conclusion
Stereo vision enables machines to perceive depth by analyzing images from multiple camera views. By generating depth maps and estimating object distances, it plays a critical role in robotics, autonomous driving, 3D reconstruction, and many other computer vision applications.