1. A method for dynamically learning a set of attributes of an operator of a point of sale (POS) comprising: receiving sensor data over a series of successive scans of a set of moving objects captured within a scan area at a POS; extracting a set of attributes from each of the set of moving objects; updating an appearance model with the set of attributes from each of the set of moving objects, wherein the appearance model comprises a visual attribute distribution and a video object distribution for each extracted attribute from each of the set of moving objects captured over the series of success scans, and wherein the appearance model further comprises a plurality of groupings of visual attribute distributions and a plurality of groupings of video object distributions identified based on a relative similarity among each of the visual attribute distributions and each of the video object distributions for each extracted attribute from each of the set of moving objects captured over the series of success scans; and analyzing the appearance model to identify a grouping from the plurality of groupings having a highest number of similar visual attribute distributions as an operator of the POS.