An advanced machine learning model that runs over a video to identify and tag human behaviors inside a retail store.
The Client was looking to build a custom AI-based solution that would allow for in-store activity supervision without breach of confidentiality.
Vid.Supervisor is a machine-learning model that runs over a video to identify and tag behaviors.
The goal is to decrease the manpower needed to codify a video via software that has a flexible fit for multiple retail business cases. In the complete solution, human input will be minimum, with only the role of reviewer remaining.
As the monotonous tasks are completed by AI, the client team will confirm the automatically assigned tags (improving the algorithm’s accuracy), while client employees can concentrate their energies on work that requires thinking and analysis.
Vid.Supervisor is ready for use in a variety of retail projects, first easing the creation of codebooks and ultimately reducing the time needed to codify a video by over 90%.
rinf.tech is working together with the client team to develop a solution leveraging the latest Machine Learning and video analytics trends.
The solution features the following capabilities: