A conservation group deploys motion-triggered trail cameras that often capture several animals in a single photo. They need software that locates each individual animal in the frame, draws a separate box around it, and labels its species, so researchers can count how many individuals of each species appear per photo. Which computer vision capability fits this requirement?
Select an answer to reveal the explanation.
Short Explanation
Picture a trail-cam photo with three deer bunched together. If the software can only slap one label on the whole picture, it might say 'deer' and call it a day, but that tells you nothing about whether there were one, three, or ten of them. Writing one sentence describing the scene has the same problem: it gives a nice summary but no way to count anything. What this conservation group actually needs is software that walks around the photo, draws a separate box around each individual animal, and tags each one with its species, the same way you'd circle and label each animal in a printed photo with a marker. That's the only approach that lets researchers tally exactly how many of each species show up, frame by frame, instead of getting one vague label for the whole image.
Full Explanation
The correct answer is A. Object detection locates each distinct object within an image, draws a bounding box around it, and assigns it a label, which is exactly what is needed to find and count multiple individual animals within a single trail-camera photo. Option B is incorrect because image captioning generates one overall descriptive sentence summarizing a whole image, such as 'a group of deer near a stream,' rather than isolating and labeling each individual animal with its own box, so it cannot support per-animal counts. Option C is incorrect because image classification assigns a single label to the entire photo, such as 'deer,' which breaks down as soon as a photo contains more than one animal or more than one species, and gives researchers no way to know how many individuals are present. Option D is incorrect because optical character recognition reads printed or handwritten text within an image, such as a sign or timestamp, and has no role in locating or labeling animals in a wildlife photo. Because the group specifically needs a count of individuals per species per photo, only a capability that isolates each animal separately meets the requirement.