Artificial Intelligence Based Determination Of Damage To Physical Structures Via Video

A method and system are provided for assessing damage to a structure. According to one embodiment, the method includes detecting one or more external parts of the structure from a video of the structure using a first machine learning (ML) module trained to identify in one or more frames of a video o...

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Bibliographische Detailangaben
Hauptverfasser:	Sati, Ankit, Barari, Adrita, Menon, Sreekanth, Jain, Payanshi, Nvs, Abhilash, Jain, Chirag
Format:	Patent
Sprache:	eng
Schlagworte:	ACOUSTICS CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES HANDLING RECORD CARRIERS IMAGE DATA PROCESSING OR GENERATION, IN GENERAL MUSICAL INSTRUMENTS PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS SPEECH ANALYSIS OR SYNTHESIS SPEECH OR AUDIO CODING OR DECODING SPEECH OR VOICE PROCESSING SPEECH RECOGNITION SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:	A method and system are provided for assessing damage to a structure. According to one embodiment, the method includes detecting one or more external parts of the structure from a video of the structure using a first machine learning (ML) module trained to identify in one or more frames of a video of a structure an external part of the structure. The method also includes using a second ML module, trained to detect and classify damaged regions of a structure from one or more frames of the video: (i) identifying one or more damaged regions of the structure, and (ii) classifying the one or more damaged regions based on damage types. The method further includes associating the one or more damaged regions and corresponding damage types with the one or more external parts, providing a respective vision-based damage estimate for each of the one or more external parts.