Object detection in computer vision refers to the task of identifying and locating objects within an image or video. The goal is to not only classify the objects present but also to determine their precise location by drawing bounding boxes around them. Object detection combines techniques from image classification, which identifies what an object is, and localization, which indicates where it is within the image. Examples include detecting people, cars, or animals in images. Modern object detection algorithms, such as YOLO (You Only Look Once) or SSD (Single Shot MultiBox Detector), have become popular due to their accuracy and speed. These models work by processing the entire image at once, allowing them to detect multiple objects in one pass. Applications of object detection include facial recognition in security systems, tracking moving objects in autonomous vehicles, and identifying defective items on assembly lines in manufacturing. Object detection is one of the most important tasks in computer vision and has wide-ranging applications across various industries.
What is object detection in computer vision?
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