Flexible multi-level regression model for prediction of pedestrian abnormal behavior
  • Jung Yu-Jin
  • Yoon Yong-Ik
Citations

WEB OF SCIENCE

0
Citations

SCOPUS

0

초록

The high incidence of heinous crime is increasing to use of CCTV. However, CCTV has been used to obtain evidence rather than crime prevention. Also it shows a weak effect about preventing crime. To solve the weak effort, we propose a Flexible Multi-level Regression (FMR) model that should estimate a dangerous situation for the pedestrian. The FMR model is tracking the behavior of between pedestrians from multiple CCTV that are located in different locations. The FMR has a prediction logic that should estimate an abnormal situation to analyze the possibility of crime by using the Regression and Apriori algorithm. The FMR model can be usefully used to prevent the crime because of an immediate response and rapid situation assessment. © Springer Science+Business Media Singapore 2016.

키워드

Abnormal behaviourBehavior predictionCCTV systemsFlexible multi-level regressionSituation assessmentComputation theoryCrimeDistributed computer systemsForecastingUbiquitous computingWireless sensor networksAbnormal behaviorAbnormal behavioursApriori algorithmsBehavior predictionCrime PreventionDangerous situationsMultilevelsSituation assessmentRegression analysis
제목
Flexible multi-level regression model for prediction of pedestrian abnormal behavior
저자
Jung Yu-JinYoon Yong-Ik
DOI
10.1007/978-981-10-0068-3_17
발행일
2016-01
유형
Article
저널명
Lecture Notes in Electrical Engineering
368
페이지
137 ~ 143