Scylla suspicious shopping behavior module is trained to spot such actions as placing items into bags, backpacks, or plastic bags.
Since detecting items being placed in pockets could result in a high number of false alerts, we currently focus on detecting actions such as placing items into bags, backpacks, or plastic bags, which are more apparent and yield more reliable results.
Yes, you can. Success is measured by the number of detected actions per trial. If a person repeatedly places objects into a bag, backpack, or plastic bag visible to the camera being processed, the accuracy would be close to 100%. However, single actions might trigger the system with slightly lower accuracy.
Scylla is a computer vision based solution that detects only the action of placing items into bags, backpacks, or plastic bags. After an alert is triggered, the attached video is reviewed by an operator, who makes the final decision.
Yes, one of the strengths of the Scylla shoplifting detection solution is its ability to detect both group and individual actions, as long as they involve placing items into bags, backpacks, or plastic bags.
The shoplifting detection system itself does not manage identities. However, this capability can be achieved by integrating it with our face recognition solution.
