Spatio-temporal data analysis plays a central role in many security-related applications including those relevant to transportation infrastructure and border security. In this paper, we investigate prospective spatio-temporal analysis methods that aim to identify "unusual" clusters of events, or hotspots, in both spatial and temporal dimensions. We propose a support vector machine-based approach and compare it with a well-known prospective method based on space-time scan statistic using three problem scenarios. The first two scenarios are based on simulated data with known hotspots. The third scenario uses a real-world crime analysis data set involving vehicles.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Prospective spatio-temporal data analysis for security informatics


    Contributors:
    Wei Chang, (author) / Daniel Zeng, (author) / Hsinchun Chen, (author)


    Publication date :

    2005-01-01


    Size :

    308752 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Prospective Spatio-Temporal Data Analysis for Security Informatics (I)

    Chang, W. / Zeng, D. / Chen, H. et al. | British Library Conference Proceedings | 2005



    Spatio-temporal segmentation of video data

    Wang, John / Adelson, Edward H. | SPIE | 1994


    SPATIO-TEMPORAL DATABASES

    Stancic, B. / Kapovic, Z. | British Library Conference Proceedings | 2010


    Spatio-Temporal Analysis of Nonrigid Motion from 4D Data

    Nastar, C. / Ayache, N. / IEEE et al. | British Library Conference Proceedings | 1994