What is Object Detection?
Object detection is a computer vision task that finds and identifies multiple objects in an image or video. It both classifies what the objects are and locates them using bounding boxes.
It builds on image classification by adding localization, predicting both object categories and their positions in the form of rectangular bounding boxes with confidence scores.
Modern approaches rely on deep neural networks, especially convolutional neural networks (CNNs), trained on large labeled datasets that include bounding-box annotations.
Popular architectures such as YOLO, SSD, and Faster R-CNN process an image in one or two stages to achieve real-time or high-accuracy detection.
Example
A security camera system uses object detection to spot people and vehicles in live footage, drawing boxes around each person and labeling them as 'person' or 'car' with confidence levels.
Why it matters
Object detection powers many real-world AI applications including autonomous driving, medical imaging analysis, retail inventory tracking, and augmented reality, making visual understanding practical at scale.
Frequently asked questions
Image classification labels the whole image, while object detection also finds where each object is located by predicting bounding boxes.
Related terms
A Convolutional Neural Network (CNN) is a specialized type of deep neural network designed to process grid-like data such as images by automatically learning spatial patterns and features.
Computer Vision is a field of AI that enables computers to interpret and understand visual information from images and videos, similar to how humans see.
Artificial General Intelligence (AGI) is a type of AI that can understand, learn, and apply knowledge across any intellectual task at a human level or beyond, rather than being limited to narrow specialties.
Artificial Intelligence (AI) is the field of computer science focused on creating machines that can perform tasks typically requiring human intelligence, such as learning, reasoning, and decision-making.
An expert system is a computer program that emulates the decision-making ability of a human expert in a narrow domain by applying a collection of if-then rules to known facts.
Image segmentation is a computer vision technique that partitions an image into multiple regions or segments by assigning a label to every pixel, typically to identify and isolate objects or areas of interest.