A retail chain installs a ceiling-mounted camera at each store entrance. The company wants software that draws a box around every person who walks through the doorway and outputs a running count of visitors per hour, without identifying who any individual shopper is. Which computer vision capability should the company implement?
Select an answer to reveal the explanation.
Short Explanation
Picture the camera feed: the store doesn't care who each person is, it just wants to know how many people crossed the threshold this hour. That's a job for a system that can spot each individual shape in the frame and put a box around it, then count the boxes. It's tempting to reach for the option that identifies specific people, but that's solving a different problem entirely, and one the retailer specifically doesn't want solved. Another wrong path assigns one single description to the whole picture, which tells you nothing about how many separate people are in it. And reading printed text off a sign has nothing to do with counting bodies moving through a doorway. The right tool here is the one built to locate and tally multiple instances of the same kind of object across a scene.
Full Explanation
The correct answer is B. Object detection identifies the location of multiple instances of an object class, such as people, within an image or video frame and can return a bounding box for each one, which is exactly what the retailer needs to locate and tally every visitor passing through the doorway each hour. Option A is incorrect because facial recognition is designed to determine or verify a specific person's identity by comparing facial features against a reference, which the retailer explicitly does not want since it only needs a count, not identities. Option C is incorrect because image classification assigns one label to an entire image, such as 'busy entrance' or 'empty entrance,' and cannot locate or count multiple individual people within a single frame the way the retailer requires. Option D is incorrect because optical character recognition extracts printed or handwritten text from an image, such as reading a sign or a receipt, and has no role in detecting or counting people walking through a doorway. Because the requirement is locating and tallying discrete people in each frame while deliberately avoiding identification, object detection is the only capability that matches both the technical need and the stated privacy constraint.