Invention Grant
- Patent Title: Identifying complex events from hierarchical representation of data set features
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Application No.: US16439508Application Date: 2019-06-12
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Publication No.: US11790213B2Publication Date: 2023-10-17
- Inventor: Yi Yao , Ajay Divakaran , Pallabi Ghosh
- Applicant: SRI International
- Applicant Address: US CA Menlo Park
- Assignee: SRI INTERNATIONAL
- Current Assignee: SRI INTERNATIONAL
- Current Assignee Address: US CA Menlo Park
- Agency: Shumaker & Sieffert, P.A.
- Main IPC: G06N3/045
- IPC: G06N3/045 ; G06N3/08

Abstract:
Techniques are disclosed for identifying multimodal subevents within an event having spatially-related and temporally-related features. In one example, a system receives a Spatio-Temporal Graph (STG) comprising (1) a plurality of nodes, each node having a feature descriptor that describes a feature present in the event, (2) a plurality of spatial edges, each spatial edge describing a spatial relationship between two of the plurality of nodes, and (3) a plurality of temporal edges, each temporal edge describing a temporal relationship between two of the plurality of nodes. Furthermore, the STG comprises at least one of: (1) variable-length descriptors for the feature descriptors or (2) temporal edges that span multiple time steps for the event. A machine learning system processes the STG to identify the multimodal subevents for the event. In some examples, the machine learning system comprises stacked Spatio-Temporal Graph Convolutional Networks (STGCNs), each comprising a plurality of STGCN layers.
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