Aug. 3, 2021
Computer vision can offer benefits to your business ranging from greater efficiency and productivity to dramatically lower expenses—but are you familiar with the different subdomains of computer vision, and which one might be right for you?
Object recognition, also known as object detection, is a subfield of AI and computer vision that, given an image, seeks to recognize the identity and location of the objects in the image. For example, given a photograph of a street scene, an AI model would return a list of annotations or labels for all the different objects in the image: pedestrians, vehicles, road signs, buildings, etc. These labels would contain both the appropriate category for each object, such as “person”, and a “bounding box,” or rectangle in which the object is completely contained.
Image recognition and object recognition are similar, but distinct, computer vision tasks. The goal of image recognition is to categorize the entire image by giving it a single label. For example, given a photograph of a dog, an image recognition model would simply return “dog” (or perhaps the dog’s breed, depending on how you trained the model). However, an object recognition model would return a label and bounding box for the dog, as well as for any other prominent objects in the image, such as a tree or a house.
Object recognition is a key task for humans: when entering a new room or scene, our first instinct is to visually assess the objects and people it contains. It makes sense, then, that it has also become a widely researched (and applied) area of computer vision. The potential use cases of object recognition span a number of industries, including:
If you’re new to the field, our computer vision glossary has dozens of definitions of computer vision terminology. Want to get started with object recognition, or another computer vision use case? Get in touch with our team of AI experts for a chat about your business needs and objectives, or sign up today with a free account on the Chooch computer vision platform.