How computer vision works
Computer vision operates through three fundamental steps:
- Acquiring an Image: Images, whether from video feeds, photographs, or 3D technology, are acquired for analysis. This can happen in real-time, involving large sets of images.
- Processing the Image: Deep learning models play a significant role in automating the processing step. These models are often trained by being exposed to thousands of labeled or pre-identified images, allowing them to learn patterns and features.
- Understanding the Image: The final step involves interpretation, where the computer identifies or classifies objects within the acquired image. This interpretative step is crucial for the application of computer vision in various fields.
Computer vision resembles a jigsaw puzzle
Computer vision operates much like assembling a jigsaw puzzle. Just as you piece together fragments to form a complete image, computers use neural networks to distinguish and identify various components of a visual image. Similar to your puzzle-solving approach, these networks recognize edges and model subcomponents. Through a series of filtering and actions within deep network layers, computers reconstruct the entire image.
In the computer vision realm, the process doesn't involve providing the computer with a final image; instead, it's often fed hundreds or thousands of related images for training. For instance, to teach a model to recognize a cat, programmers upload millions of cat photos. The model then autonomously learns the distinctive features, like whiskers, tails, and pointy ears, that collectively define a cat.
Why Is Computer Vision Important?
Computer vision has been a significant area of research since the 1950s, and its importance continues to grow, with various applications across industries. According to the deep learning research group BitRefine, the computer vision industry is expected to reach nearly 50 billion USD in 2022, with a significant portion of the revenue, 75 percent, coming from hardware.
The significance of computer vision lies in the escalating need for computers to comprehend the human environment. Achieving this understanding is facilitated by enabling computers to "see" in a manner analogous to human vision. This becomes especially crucial as we advance towards developing more sophisticated AI systems that emulate human-like capabilities. The applications of computer vision span a wide range of fields, making it a pivotal technology in our increasingly interconnected and technologically driven world.