Wang et al., 2019 - Google Patents
RETRACTED ARTICLE: Abnormal event detection with semi-supervised sparse topic modelWang et al., 2019
- Document ID
- 10658116518181643083
- Author
- Wang J
- Xia L
- Hu X
- Xiao Y
- Publication year
- Publication venue
- Neural Computing & Applications
External Links
Snippet
Most research on anomaly detection has focused on event that is different from its spatial– temporal neighboring events. However, it is still a significant challenge to detect anomalies that involve multiple normal events interacting in an unusual pattern. To address this …
- 238000001514 detection method 0 title abstract description 47
Classifications
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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- G06F17/30781—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F17/30784—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre
- G06F17/30799—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre using low-level visual features of the video content
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- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
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