1. A computer-implemented method, comprising: retrieving depth data from a sensor, the depth data describing distance information associated with one or more objects detected by the sensor; clustering the depth data to determine two or more candidate leg clusters, each candidate leg cluster including a portion of the depth data that may represent a human leg detected by the sensor; identifying a candidate leg cluster pair based on the two or more candidate leg clusters, the candidate leg cluster pair including two candidate leg clusters within a certain distance between each other, the two candidate leg clusters including center points and neighbor points surrounding the center points; propagating from the center points of the two candidate leg clusters included in the candidate leg cluster pair upwards to the neighbor points of the two candidate leg clusters that are represented by portions of the depth data; determining a connectivity between the neighbor points of the two candidate leg clusters; responsive to determining the connectivity between the neighbor points of the two candidate leg clusters, determining that there is a connectivity between the two candidate leg clusters included in the candidate leg cluster pair; and responsive to determining that there is the connectivity between the two candidate leg clusters included in the candidate leg cluster pair, determining that the candidate leg cluster pair is qualified to be a leg cluster pair representing a person detected by the sensor.