The technology works best where there is a stable scene to evaluate — meaning one produced by a fixed camera or a pan-tilt camera with established pre-sets. The technology can be applied to megapixel cameras, but the sheer volume of data increases the required computational power unless the scene is downsized or down-sampled. Also, certain one-off or never seen before events may be a challenge, when the scene has not had enough longevity to allow any meaningful learning to have taken place.
Learning “normalcy” can potentially provide valuable information about trends, such as time of day activity, flow density, and dynamics associated with particular events. Also, the data analyzed and learned does not necessarily need to come from video, but almost any sensor from which analysis and metadata generation can be accomplished.
We are not likely to see the human assessment step eliminated anytime soon, but the more that human brain can move from the mundane to the exceptional, the more productive it can be.
Ray Coulombe is Founder and Managing Director of SecuritySpecifiers.com, enabling interaction with specifiers in the physical security and ITS markets; and Principal Consultant for Gilwell Technology Services. He can be reached at ray@SecuritySpecifiers.com or through LinkedIn or followed on Twitter at RayCoulombe.