Subject-tracking in a cashier-less shopping store for autonomous checkout for improving item and shelf placement and for performing spatial analytics using spatial data and the subject-tracking

A method for predicting a path of a subject in an area of real space, the method including:

• using a plurality of sensors to produce respective sequences of frames of corresponding fields of view in the real space;
• identifying, for a particular subject, a determined path in the area of real space over a period of time using the sequences of frames produced by sensors in the plurality of sensors, the determined path including a subject identifier, one or more locations in the area of real space and one or more timestamps;
• accumulating multiple determined paths for multiple subjects over a period of time;
• generating a transition matrix using the accumulated determined paths, wherein an element in the transition matrix identifies a probability of a new subject moving from a first location to at least one of other locations in the area of real space;
• and
• predicting the path of the new subject in the area of real space in dependence on an interaction of the new subject with an item associated with the first location in the area of real space, wherein the predicting of the path comprises identifying a second location, from the other locations included in the transition matrix, having a highest probability associated therewith with respect to movement of the new subject from the first location.

A non-transitory computer readable storage medium impressed with computer program instructions to predict a path of a subject in an area of real space, the instructions, when executed on a processor, implement a method comprising:

• using a plurality of sensors, producing respective sequences of frames of corresponding fields of view in the real space;
• identifying, for a particular subject, a determined path in the area of real space over a period of time using the sequences of frames produced by sensors in the plurality of sensors, the determined path including a subject identifier, one or more locations in the area of real space and one or more timestamps;
• accumulating multiple determined paths for multiple subjects over a period of time;
• generating a transition matrix using the accumulated determined paths, wherein an element in the transition matrix identifies a probability of a new subject moving from a first location to at least one of other locations in the area of real space;
• predicting the path of the new subject in the area of real space in dependence on an interaction of the new subject with an item associated with the first location in the area of real space, wherein the predicting of the path comprises identifying a second location, from the other locations included in the transition matrix, having a highest probability associated therewith with respect to movement of the new subject from the first location;
• and
• changing placement of a particular item, in dependence on the predicted path, from an existing location to a new location in the area of real space to increase interaction of subjects with the particular item.