Modern smartphones provide an ideal foundation for integrating computer vision into mobile applications. Due to high-resolution cameras, depth sensors, and powerful processors, they have the power to manage complex computer vision tasks efficiently. The rising demand for features like object recognition, image search, and Augmented Reality experiences drives this evolution. The article explores the various applications and benefits of computer vision in mobile apps across business domains.
E-commerce
E-commerce is pioneering in the introduction of сomputer vision in their applications. It’s a way to enhance the shopping experience and increase customer engagement. Users demonstrate a longer time staying on the E-commerce platform due to the combination of the purchasing process with entertainment.
- A visual search feature allows users to find products using images rather than entering text queries. Besides a more engaging experience, it reduces search friction and increases conversion rates. Customers can use photos or screenshots to find desired products across the digital stores. Imagine spotting an item you like somewhere and being able to instantly find and order the same or a similar product. Moreover, the visual search function captures user intent more accurately, enabling e-commerce platforms to provide better product recommendations and personalized shopping experiences.
- Augmented Reality (AR) provides virtual try-on opportunities that bridge the gap between online and in-store shopping. Customers can try clothes, accessories, makeup, and home decor using their smartphone cameras. They see how selected products will look on them or in a real environment. Great examples are Sephora’s Virtual Artist app for makeup and IKEA’s app for placing virtual furniture in users’ spaces. By providing a more accurate representation of how products will look and fit, AR can help customers make better-informed purchasing decisions, thereby reducing the likelihood of returns due to unmet expectations.
Healthcare
In healthcare, computer vision is mainly known for analyzing medical images in diagnostics and 3D visualizations in surgeries. However, mobile apps also can extend their capabilities.
- In telemedicine, computer vision expands the possibilities of remote diagnostics and virtual сonsulting. Apps can assess patient symptoms such as conditions of skin and eyes, rashes, movements, and other visible signs of illness. This visual assessment aids doctors in making more informed decisions during these online meetings. Additionally, these apps can facilitate remote monitoring of chronic conditions by analyzing daily visual data recorded by patients.
- Fitness apps that are aimed at health and wellness can use сomputer Vision to analyze users’ physical activities and provide feedback on their technique right at the moment. It reduces the risk of injury and improves the overall workout effectiveness. Users get smart training right at home. For example, FitWise technology by OpenCV.ai utilizes a custom AI model to analyze users’ movements in 3D for advanced motion tracking.
Automotive
In the automotive industry computer vision mobile apps aim to enhance drivers’ safety and streamline various processes. Technology opens opportunities for quite interesting use cases, going beyond license plate recognition.
- Being a part of driver assistance and safety, the app can monitor the driver’s facial expression and detect signs of drowsiness, absent-mindedness, or inattention. If the computer vision algorithm detects the driver falling asleep or not paying attention to the road, the app takes action. For example, sending warnings, loud noises or even vibration of the steering wheel.
- In case of a car accident, it is necessary to conduct an accurate assessment of all damages. Drivers can use mobile apps to photograph vehicle damage. Computer vision algorithms analyze these images to assess the extent of damage, and the cost of repairs. This reduces the need for physical inspections and speeds up the claims settlement. Also, when renting a car, it can be checked for external damage. An objective assessment has a positive impact on the cost of repairs or penalties.
Education
Computer vision makes the educational process more interactive, engaging, and personalized. This approach may help learners grasp complex concepts more effectively. Using AR technology apps can overlay 3D models onto the real world, allowing students to explore different courses like for example, biology, history, and geography.
Imagine a high-fidelity model of the human heart, which they can also interact with. Traditional textbooks also can be combined with AR. Students can point their mobile devices at specific pages to see animations, videos, or additional interactive content that explains the concepts in more depth. And when learning a language, the user can point the camera at an object and the application will show a word in a foreign language.
Entertainment
Computer vision offers innovative ways for users to engage with content and brings new dimensions to the entertainment experience. One prominent use case is AR gaming.
We all remember the popularity of Pokémon GO when players saw and interacted with virtual creatures in real-world environments through their smartphone cameras. Another example is social media and photo editing. Apps employ computer vision to provide real-time face filters and effects. Users apply various transformations and animations to their faces for video and photo sessions. Technology can change not only faces but also the space around them from dynamic background changes to complex 3D elements.
The future of mobile applications
Computer vision in mobile applications is rapidly evolving, due to advancements in hardware, software, and AI algorithms. The ongoing development of ARKit (Apple) and ARCore (Google) components enables mobile apps to offer more sophisticated and stable AR experiences. More powerful mobile processors enable real-time object detection and recognition directly on the device. This reduces the time between capturing an image and processing it. Thus applications better understand the environment and provide a smoother and more responsive user experience with better interactions.
Custom-trained models and transfer learning enable more precise and application-specific object recognition across different industries. This advancement also has significant implications for accessibility like real-time text recognition for visually impaired users, sign language recognition, and gesture-based controls. Technologies are becoming more inclusive and user-friendly.
By integrating computer vision into their infrastructure, businesses can enhance the performance of their software products and elevate their services to new heights. Different studies show that companies implementing computer vision technologies have seen up to a 30% increase in operational efficiency.
Final words
Advancements in AI technologies blur the boundaries between the physical and digital worlds. This leads to the emergence of innovative mobile app functionalities, that hold immense potential for businesses. Guide “Computer vision applications in your smartphone” by computer vision firm OpenCV.ai shows prime examples of how cutting-edge technology fulfills users’ needs and enhances their experience. As these applications become more sophisticated, they are poised to revolutionize all industries from e-commerce and healthcare to security and entertainment.