AI Perception

Computer Vision: From Geometries to Meaning Computer vision has moved from counting pixels to understanding what a scene means. Early work relied on geometry—camera models, calibration, and the relations between views. Algorithms used feature matching and 3D reconstruction to estimate space. They could locate objects, but they did not always explain why those objects mattered to people. The shift from geometry to meaning comes from data, better learning models, and a goal to build systems that interpret rather than only measure images. ...

Seeing with AI Computer Vision in Autonomous Systems Seeing with AI computer vision means machines interpret what they see through cameras and other sensors. In autonomous systems, this ability helps devices understand the world, make decisions, and act safely. AI vision combines live image data with intelligent models that detect objects, estimate distance, and track changes over time. The result is a perception layer that supports navigation, inspection, and interaction in real environments. ...