A Fast Laser Motion Detection and Approaching Behavior Monitoring Method for Moving Object Alarm System (MOAS) | Zendy

Haiwei Dong | Zendy; Nikolas Giakoumidis | Zendy; Joseph B Juma | Zendy; Dmitriy A Tretyakov | Zendy; Nikolaos Mavridis | Zendy

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A Fast Laser Motion Detection and Approaching Behavior Monitoring Method for Moving Object Alarm System (MOAS)

Author(s) -

Haiwei Dong,

Nikolas Giakoumidis,

Joseph B Juma,

Dmitriy A Tretyakov,

Nikolaos Mavridis

Publication year - 2012

Publication title -

procedia engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.32

H-Index - 74

ISSN - 1877-7058

DOI - 10.1016/j.proeng.2012.07.239

Subject(s) - alarm , computer vision , computer science , object (grammar) , artificial intelligence , object detection , tracking (education) , motion (physics) , real time computing , motion detection , grid , false alarm , boundary (topology) , engineering , pattern recognition (psychology) , geography , mathematics , geodesy , psychology , mathematical analysis , pedagogy , aerospace engineering

It is very dangerous for elderly people or workers to be hit or even knocked down from fast moving object moving behind them. To avoid such circumstances, we want to build a Moving Object Alarm System (MOAS). This paper focuses on obtaining a fast solution to monitor the moving behavior of the objects by laser for MOAS. Compared with previous work in motion detection and tracking, we are interested especially in monitoring the approaching behavior of such objects, and quickly providing an alarm in the case the situation is dangerous. A boundary within which the objects are monitored was defined. Under this assumption, fan-shaped grid was chosen to get special partitioning. Based on our algorithm, continuous objects can be detected with very high efficiency. By updating a deviation matrix, the object association solution can also be quickly found. Three categories of outdoors experiments were performed: objects passing, approaching as well as crossing, which empirically verified the effectiveness of our proposed method

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