Disparity Map
A disparity map is a 2D image or grid where each pixel value represents the horizontal displacement (disparity) between corresponding points in a pair of stereo images, typically used in computer vision and robotics. It quantifies the difference in pixel coordinates for matching features from left and right camera views, enabling depth perception through triangulation. This concept is fundamental for applications like 3D reconstruction, autonomous navigation, and augmented reality.
Developers should learn about disparity maps when working on stereo vision systems, as they are essential for estimating depth from images without specialized hardware like LiDAR. Use cases include building depth-sensing cameras for robotics, creating 3D models from photographs, or implementing obstacle detection in self-driving cars. It's particularly valuable in fields requiring cost-effective spatial awareness, such as virtual reality or medical imaging.