@article{ref1,
title="Assessment of abnormal detection technology aimed for the clarification of the causes of falls in public area",
journal="Japanese journal of fall prevention",
year="2014",
author="Kobayashi, Yoshiyuki and Yanagisawa, Takafumi and Sakanashi, Hidenori and Nosato, Hirokazu and Takahashi, Eiichi and Mochimaru, Masaaki",
volume="1",
number="1",
pages="55-63",
abstract="The objective of this study was therefore, to develop a system that can automatically identify scenes of a video in which falling occurs. A surveillance camera was placed in our laboratory for a two-month period to record the daily activities of employees, after which one real tripping scene and 28 normal walking scenes of various employees were manually identified. Using this scenes two different models to detect scenes in which tripping occurred were build; 1) a model based on scenes of walking persons not carrying any baggage, and 2) a model using scenes of walking persons with and without baggage. Based on these two models real tripping scenes can be identified as scenes with abnormal motions. If solely the first model is used, scenes in which a person carries baggage is also considered to be an abnormal scenes. If the second model is used scenes in which a person is carrying baggage are not considered to be abnormal. This indicates that the second model can be used to automatically obtain scenes in which falls occur, allowing for time efficient analyzing of captured videos.</p>   <p>Language: ja</p>",
language="ja",
issn="2188-5702",
doi="10.11335/tentouyobou.1.1_55",
url="http://dx.doi.org/10.11335/tentouyobou.1.1_55"
}