Invention Application
US20120301105A1 SYSTEMS AND METHODS FOR RETRIEVING CASUAL SETS OF EVENTS FROM UNSTRUCTURED SIGNALS
有权
用于从非结构化信号中检索休闲活动的系统和方法
- Patent Title: SYSTEMS AND METHODS FOR RETRIEVING CASUAL SETS OF EVENTS FROM UNSTRUCTURED SIGNALS
- Patent Title (中): 用于从非结构化信号中检索休闲活动的系统和方法
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Application No.: US13427610Application Date: 2012-03-22
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Publication No.: US20120301105A1Publication Date: 2012-11-29
- Inventor: James M. Rehg , Karthir Prabhakar , Sangmin Oh , Ping Wang , Gregory D. Abowd
- Applicant: James M. Rehg , Karthir Prabhakar , Sangmin Oh , Ping Wang , Gregory D. Abowd
- Applicant Address: US GA Atlanta
- Assignee: Georgia Tech Research Corporation
- Current Assignee: Georgia Tech Research Corporation
- Current Assignee Address: US GA Atlanta
- Main IPC: H04N5/91
- IPC: H04N5/91

Abstract:
A method for providing improved performance in retrieving and classifying causal sets of events from an unstructured signal can comprise applying a temporal-causal analysis to the unstructured signal. The temporal-causal analysis can comprise representing the occurrence times of visual events from an unstructured signal as a set of point processes. An exemplary embodiment can comprise interpreting a set of visual codewords produced by a space-time-dictionary representation of the unstructured video sequence as the set of point processes. A nonparametric estimate of the cross-spectrum between pairs of point processes can be obtained. In an exemplary embodiment, a spectral version of the pairwise test for Granger causality can be applied to the nonparametric estimate to identify patterns of interactions between visual codewords and group them into semantically meaningful independent causal sets. The method can further comprise leveraging the segmentation achieved during temporal causal analysis to improve performance in categorizing causal sets.
Public/Granted literature
- US08909025B2 Systems and methods for retrieving causal sets of events from unstructured signals Public/Granted day:2014-12-09
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