Patent ID: 8958602
Filing Date: 2015-02-17
Classification: G06K,G06T,H04N

Abstract:
1. A method comprising the steps of: receiving at least one video input containing a plurality of video frames; performing an anomaly detection function comprising the steps of designating a plurality of sub-frames within each of the plurality of video frames wherein each of the plurality of sub-frames has a quasi-unique grid location within the plurality of video frames, calculating a signal-to-noise ratio value for each of the plurality of sub-frames, and comparing the signal-to-noise ratio value for each of the plurality of sub-frames to a signal-to-noise threshold value to identify anomalous sub-frames and non-anomalous sub-frames; performing a cluster detection algorithm to identify at least one cluster wherein the at least one cluster is comprised of at least two of the anomalous sub-frames, wherein the anomalous sub-frames are adjacent; instantiating an anomaly object, wherein the anomaly object is a data structure which includes at least one property corresponding to at least one cluster property; performing at least one filtering algorithm to compare at least one property of the anomaly object to at least one threshold value and discarding an anomaly object if the filtering algorithm indicates a risk of false detection; updating a risk value property of each the anomaly object that is not discarded to indicate that the anomaly object is a tracked anomaly object; incrementing the number of frames property each time the tracked anomaly object appears in at least one video frame; updating the risk value property of the tracked anomaly object to indicate that the tracked anomaly object is a target object when the number of frames property exceeds a consecutive frames threshold value; updating at least one location coordinate property value for the target object; and updating properties of the at least one video input to create an annotated video output.