Top 5 Computer Vision Applications in Artificial Intelligence

Applications of Computer Vision

Introduction

The ongoing refinement and research in the intersecting field of AI and computer vision are triggering the dopamine of researchers across the globe. Researchers and developers are doing rigorous research and development in computer vision and artificial intelligence to help bring new applications into action. These two domains can work together to give machines a perception of sight & an understanding of what these machines are seeing. This article will take you through the top 5 computer vision (CV) applications in Artificial Intelligence (AI).

What is computer vision?

Computer vision is a branch of computer science that blends the potential of digital image processing (DIP) and artificial intelligence (AI). This domain uses machine learning and deep learning on unstructured data (images and video frames) to render computers a perception to understand things in their ecosystem through the camera and other visions. Through computer vision, developers can enable machines to recognize, determine, and analyze a photo, video frame, or motion object the same way humans do. This domain is rapidly gaining popularity due to its cutting-edge requirements and innovation in implementing remote monitoring, driverless cars, modern robots, auto-inspection systems, etc.

Things required for developing a Computer Vision system/application in AI

To create a computer vision system or application, the basic set of technologies and devices are:

i. A camera or multiple cameras to obtain data

ii. Machine learning and deep learning algorithms to train for classification of what the camera is seeing

iii. Basic programming logic with iterations to automate the tasks endless times

Top 5 Computer Vision Applications in Artificial Intelligence

Here’s a list of the top 5 computer vision applications that work with AI to provide outstanding performance in different domains.

· Autopilot mode in Tesla: Tesla’s modern automated cars have advanced convenience and safety features that use computer vision and artificial intelligence algorithms to manage cumbersome driving operations. The autopilot algorithm in these cars can steer the car, put the brakes, and accelerate automatically based on the vision it sees via its rear cameras. There are 8 (mostly) different cameras that work in close tandem to provide a clear computer vision and act as per the machine learning and deep learning algorithms.

If it sees an object or a pedestrian, it will automatically put the brakes, and when the lane is empty, it will accelerate as per the passenger’s requirement. Tesla leverages multiple AI algorithms that respond in real-time, seeing through computer vision (its eight cameras), called Neural Net Planner. This Neural Net Planner works dynamically to understand traffic behavior, provide actual trajectory routing, and control other actions/sudden actions that are part of a driving lifecycle.

· Productivity Analytics: Another computer vision application that’s gaining popularity in manufacturing and other sectors is productivity analysis tracking. This application brought a revolutionary change in how workplace monitoring used to happen. With the help of such applications, organizations can check how employees are spending their time and resources for implementing various tools.

Such an application uses cameras and computer vision with AI-driven algorithms to monitor employee work. The data it extracts can also help to provide valuable insight into workplace collaboration, time management, and employee productivity. These application data also help organization executives perform lean management strategies to quantify work progress through the cameras-based vision system and AI algorithms.

· Detecting tumors and visualizing pathologies: Another field where computer vision & AI-based applications are gaining massive recognition is the Healthcare industry. Microsoft’s InnerEye and applications like these help doctors read 2D and 3D images and render them for detecting tumors. Algorithms that blend computer vision and AI can also help in cancer screening, medical imaging, and complete body diagnostics.

Ultrasound-based visual applications can also help doctors detect pathological abnormalities. Such applications often use OpenCV and Streamlit framework to process images with different heatmaps and opacities. Researchers train the machine learning algorithms with previous images & 3D models of tumors, pathological abnormalities, and similar other issues so that the system’s visual can efficiently identify and classify them and accurately detect the flaws in the human body.

· Traffic flow analysis and AI Traffic light: Pedestrian detection or tracking of humans on the road and based on that, the traffic light will work smartly is another significant application of computer vision with AI. Numerous smart cities are introducing this smart traffic light that leverages multiple small cameras with machine learning algorithms to identify pedestrians.

Furthermore, various private firms are also taking initiatives to create pedestrian protection systems/applications that can recognize & determine humans based on variations like body attire, structure, background clutter, illuminance, etc. It helps in moving safely on roads. Such apps also come with alert and notification systems if it detects an accident. The app will instantly notify the traffic police to take proactive action and rescue those humans from a mishap.

· Livestock health monitoring: Livestock farming and maintaining them is a challenge for most livestock businesses. That is why some companies came up with computer vision applications that can 24x7 monitor livestock animals’ health and behavior. These applications help livestock business owners to monitor their actions remotely in real time. These applications use multiple cameras that work consecutively with AI algorithms to understand each one of them individually. These applications also come with data analysis and behavior analysis algorithms to identify if any animal faces health issues or other problems. These apps can prompt immediately in case, an animal is about to give birth or is doing unusual behavior. These apps can also leverage IoT systems and sensors to keep a record of environmental conditions.

Conclusion

The use of computer vision is endless irrespective of the sector where we can use it. We hope this comprehension has given you a crisp idea of the top five computer vision with AI, data science, & IoT projects that every aspirant should know. This article covered five different applications from different verticals.