Summarisation of anomalies in video data
OwnerEdward Ronald MAUSER, Kamal NASROLLAHIinventors
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OwnerEdward Ronald MAUSER, Kamal NASROLLAHIinventors
Estimating the term…
The disclosure provides in a first aspect a computer-implemented method of summarising video anomalies in video data, the method comprising: receiving video data from one or more video surveillance cameras; performing Video Anomaly Detection, VAD, for detecting one or more anomalies in the video data; and summarising the one or more anomalies by generating at least one composite representation that comprises a background on which one or more visual elements are overlaid, wherein the background represents at least a part of a physical area, and the one or more visual elements respectively represent a preview of at least one anomaly at a location in the said physical area where the at least one anomaly was detected.
A computer-implemented method of summarising video anomalies in video data, the method comprising:
The method according to the preceding claim, the method comprising executing a user instruction for selecting the video surveillance cameras for which the composite representations are to be generated.
The method according to the preceding claim, wherein the user instruction is an instruction to select all video surveillance cameras for which at least one anomaly was respectively detected.
A non-transitory computer readable storage medium storing instructions that, when executed, configure a processor to perform a method of summarising video anomalies in video data, the method comprising:
A video processing apparatus, comprising at least one processor configured to:
The apparatus according to the preceding claim, wherein to perform VAD involves performing Open-Set Recognition, OSR, using a Machine Learning, ML, model, trained on video data including normal behaviours or objects.
Dependencies are inferred from the claim text.