The role of computer vision in Augmented Reality: Understanding the technology behind AR
Imagine stepping into a world where digital elements blend with the real environment around you. This is the power of Augmented Reality (AR), a technology that has the potential to transform the way we interact with the digital world. According to a report, the global AR market size is expected to grow from $62.75 billion in 2023 to $1,109.71 billion by 2030, at a CAGR of 50.7% during the forecast period. These stats demonstrate the growing application of augmented reality for industries.
At the heart of this technological revolution lies computer vision, a field that enables computers and systems to derive meaningful information from digital images, videos, and other visual inputs — and take recommendations or actions based on that information. If we talk about the computer vision market, the global market size was valued at $9.45 billion in 2020 and is projected to reach $41.11 billion by 2030, at a CAGR of 16.0% from 2020 to 2030.
In this article, we will delve into the pivotal role of computer vision in shaping the landscape of augmented reality. However, first, let’s understand these technologies in detail.
What is augmented reality?
Augmented reality is a cutting-edge technology that seamlessly integrates digital content and information into a real-world environment. There are a number of benefits of augmented reality. Through the use of devices such as smartphones, tablets, AR headsets, or smart glasses, users can experience a merged world where computer-generated elements co-exist with the physical world in real-time.
For instance, IKEA uses AR to help shoppers visualize and test products in their own space before making a purchase. It offers multiple tools for customer needs like the IKEA Place app that superimposes to-scale models of furniture in real-life rooms or the IKEA home planner that helps build furniture sets, like kitchen cabinets, to ensure they are satisfied before placing an order. There are a number of augmented app reality development companies that can help you integrate this technology into your products and services.
What is computer vision?
Computer vision AR focuses on enabling machines to interpret and understand the visual world, much like humans do. It involves developing algorithms and techniques that allow users to process and visualize images to process the virtual environment, extract meaningful insights, and make informed decisions based on visual data.
For instance, consider an example of a self-driving car equipped with computer vision AR technology. As the car navigates through the busy roads of an urban city, its cameras capture a continuous stream of images.
The computer vision system processes these images in real time to identify various objects and make sense of the road environment. It can detect pedestrians crossing the street, recognize traffic signs and signals, differentiate between cars and motorcycles, and assess the distance and relative speed of nearby vehicles. In this scenario, computer vision is the technology that allows self-driving cars to ‘’see’’ and ‘’understand’’ the road scene.
The role of computer vision in AR
Computer vision plays a transformative role in AR, as it forms the foundation of how digital content is seamlessly integrated into the real-world environment. Below we have listed a few ways in which computer vision is contributing to the field of AR.
1)Object recognition: Computer vision in augmented reality serves a pivotal role by identifying and detecting real-world objects, seamlessly integrating virtual elements into them. This process, known as object detection, is a fundamental aspect of crafting immersive and lifelike AR experiences. The procedure unfolds as cameras capture images or videos of the user’s surroundings, which are then swiftly scrutinized by real-time computer vision algorithms.
These sophisticated algorithms harness techniques such as edge detection, pattern recognition, and machine learning to discern objects based on their visual attributes — comprising size, form, and hue. Once an object is successfully identified, AR systems can overlay virtual content onto it. This content might encompass diverse elements, from dynamic 3D models and animations to informative textual displays, enriching the user’s perception of reality with digital enhancements.
2) Localization and mapping (SLAM): Augmented reality computer vision plays a pivotal role in simultaneous localization and mapping (SLAM), a technique that enables AR devices to understand their own position and orientation within the environment in real-time. This is essential for ensuring that virtual content aligns correctly with the user’s perspective as they move around. SLAM helps AR experiences remain stable and accurate, even in dynamic environments.
For instance, you are wearing a headset in a museum. As you move, the headset uses computer vision, the technology behind augmented reality, to understand where you are and what you are looking at. This process, called SLAM, helps the headset create a map of the museum and know its own position. When virtual content, like a guide, appears next to an exhibit, SLAM ensures that the virtual content stays in the right place even as you move around. This makes the AR experience stable and accurate as if the virtual and real worlds are perfectly connected.
3) Gesture and motion recognition: Computer vision allows AR systems to track user gestures, facial expressions, and body movements. This tracking enables users to interact naturally with virtual content. For instance, users can manipulate virtual objects using hand gestures, enhancing the interactive aspect of augmented reality technology.
4) Depth estimation: Computer vision assists in estimating the depth of objects in the environment, enabling AR devices to understand the three-dimensional layout of the scene. This depth information is crucial for placing virtual objects at the correct distances, ensuring they appear realistically integrated into the physical space.
5) Environmental adaptation: In the world of Augmented Reality technology, making virtual objects feel like they belong in the real world is all about adapting to the environment. This is where computer vision comes into play. Imagine seeing virtual objects that react to changes in lighting, behave like real ones in reflections, and cast lifelike shadows.
Computer vision helps AR systems understand the visual cues around them, like how light falls and how objects look. So, when you step from a bright room to a dim one, the virtual stuff in your AR world also adjusts to match the new lighting. This creates a more natural and immersive experience where the digital and real blend seamlessly.
Conclusion
The amalgamation of computer vision and augmented reality technology has ignited a remarkable transformation in how we perceive and interact with the world. As we navigate the future of AR and VR, we are accompanied by the powerful presence of computer vision, seamlessly bridging the gap between the physical and the digital world.
Computer vision gives our digital companions the ability to see the world just like we do. As computer vision technology gets better, the future of augmented reality becomes more and more like real life, making us feel like we’re stepping into a world where what we imagine and what’s real come together in amazing ways. In case you want to know more about these technologies, you can consult reputable AR app development companies. The experts will guide you through the whole process and help you understand better.
