Exploring discriminative features for anomaly detection in public spaces
Context data, collected either from mobile devices or from user-generated social media content, can help identify abnormal behavioural patterns in public spaces (e.g., shopping malls, college campuses or downtown city areas). Spatiotemporal analysis of such data streams provides a compelling new app...
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| Main Authors: | , , , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2015
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/3138 https://ink.library.smu.edu.sg/context/sis_research/article/4138/viewcontent/P_ID_52611_SPIE_2015_LocationBasedAnomaly.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
