Solutions Built with Computer Vision

People counting with the aid of machine learning algorithms can be useful to retailers in assessing store’s success and improving footfall. Tracking human movement in stores can also provide insight into shopper engagement and store layout optimization. Loitering or accessing off-limit areas can be flagged to prevent theft and other unauthorized activities.

Using computer vision to count the shoppers in a waiting line and alert when a threshold is reached enables retail staff to open new counters and manage checkout faster. Self-checkout systems with computer vision-powered cameras automatically recognize products and process them, improving both customer experience and security while speeding up the whole process.

Computer vision technology helps to minimize false positives and avoid needless procedures and treatments. Trained machine learning algorithms can classify cells and detect even the slightest presence of a condition, contributing to medical diagnosis with high levels of precision. Disease identification and early detection with the help of image recognition has significantly improved cancer prognosis.

Medical robots capable of high-definition 3D imaging aid accurate depth perception in minimally invasive procedures. Mechanical arms fitted with surgical instruments and cameras can be operated by doctors via a console where they view the magnified surgical site.

AI-powered defect detection systems gather data in real-time and compare it with predefined quality standards to identify defects and ensure an error-free production line. With computer vision-based systems constantly monitoring the manufacturing environment and equipment based on various metrics, maintenance can also be carried out proactively.

Adherence to safety standards can be strictly enforced using computer vision technology which detects even minor compliance violations and raises alerts. Intelligent monitoring systems also facilitate inspection of remote assets and work sites without compromising workers’ safety.

Computer vision technology can be used to detect complex events like bad tackle or foul play in real time during a game. Camera-based systems can support referees in determining whether a goal has been scored or not.

Player pose tracking with AI vision can be used to detect the style of an athlete and when combined with data from wearables can help in assessing their performance. Stroke recognition applications that are capable of detecting and classifying strokes aid coaches and players to analyze games and improve skills.

Computer vision has been long employed in vehicle classification and there are specialized deep learning-based solutions for safety monitoring and productivity assessment in construction vehicles.

The technology is also used by law enforcement agencies to automatically detect rule violations such as speeding, illegal turns, and wrong-way driving. Other applications include autonomous navigation, detection of parking lot occupancy, traffic analysis, road condition monitoring, pedestrian detection, and collision avoidance systems.