1. A computer-implemented method for smart labeling at scale of motion detected events in video surveillance, comprising the steps of: at a server, labeling at least one zone of a source image, said source image from a source camera of a plurality of source cameras, and storing said label zone by: receiving said source image with a corresponding upload token, wherein said upload token contains data identifying said source camera and an end user entity; upon authorizing and using said upload token, presenting said source image to said end user entity for labeling; and receiving at least one label name of said at least one zone of said source image, correlating said at least one label name with said at least one zone for said source image, and storing said correlated labeled zone; and at a server in real time, processing label hits for incoming images from a plurality of source cameras, said plurality comprising said source camera, said processing by: receiving and decrypting an encrypted token that uniquely identifies said end user entity and said source camera; upon authorizing said decrypted token, receiving at least a first incoming image frame, and at least a second incoming image frame from said source camera; comparing one or more objects on said at least second incoming image frame with one or more objects on said at least first incoming image frame and identifying significant motion based on said comparison, wherein significant motion is identified in part by computing a delta of change between any of said objects on said at least second incoming image frame and said objects on said at least first incoming image frame; for each identified significant motion, determining a motion zone, wherein said motion zone is the zone of said at least second incoming image frame on which said significant motion overlays; for each motion zone: computing an amount of an overlap with a candidate labeled zone from said stored correlated labeled zones; and measuring said overlap among said motion zone and said labeled zone, determining therefrom whether further granular analyses are required to be performed, and performing said further granular analyses when required; generating and indexing a label hit for each matching motion zone with candidate labeled zone; and generating tasks for each generated label hit; wherein at least one of the steps is performed by a processor.