Object Detection is a computer vision task that not only identifies what objects are in an image but also locates where each one is, usually by drawing a box around it.
What it means in plain English
Simple image classification answers “what is in this picture?” Object detection goes further: it finds every object of interest, labels each, and marks its position. This ability to identify and locate multiple objects at once is what makes vision systems useful for the real world, where a scene contains many things that all matter.
It works on both still images and live video.
A simple example
A self-driving car’s vision system uses object detection to simultaneously spot and locate pedestrians, other cars, traffic lights, and road signs in its camera feed — knowing not just that they exist but exactly where each one is.
Why it matters
Object detection is fundamental to applications like autonomous vehicles, security cameras, retail analytics, and industrial inspection. Locating objects, not just recognising them, is what lets AI systems act on what they see.
Related terms
- Computer Vision — the field object detection belongs to.
- Image Segmentation — a more detailed, pixel-level version.
- Convolutional Neural Network — often used for object detection.
Frequently asked questions
What is object detection?
It is a computer-vision task that both locates objects in an image (usually with bounding boxes) and identifies what they are.
How is it different from image classification?
Classification labels a whole image with one category; object detection finds and labels multiple individual objects and where they are within the image.
