Automated estimation of elder activity levels from anonymized video data.
Automated estimation of elder activity levels from anonymized video data.
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根据匿名视频数据自动估计老年人的活动水平。
DOI：
10.1109/iembs.2009.5335248
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
He,Zhihai
中科院分区：
文献类型：
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作者：
Harvey,Nicholas;Zhou,Zhongna;Keller,JamesM;Rantz,Marilyn;He,Zhihai
辅助生活社区中老年人生活质量的显着下降通常是由健康事件引发的。如果有必要的信息，这些事件通常是可以预测的，因此可以避免或降低严重程度。日常生活活动和长期活动水平的统计数据为功能评估和健康预测提供了重要数据。然而，持续的活动监控和持续收集此类数据是极其劳动密集型的，耗时且成本高昂。在这项工作中，我们提出了一种方法，用于自动估计活动水平的基础上从视频数据分割的轮廓，并随后提取高阶信息的轮廓。通过从这些高阶信息建立回归模型，我们的系统可以自动估计老年人的活动水平。
Significant declines in quality of life for elders in assisted living communities are typically triggered by health events. Given the necessary information, such events can often be predicted, and thus, be avoided or reduced in severity. Statistics on activities of daily living and activity level over an extended period of time provide important data for functional assessment and health prediction. However, persistent activity monitoring and continuous collection of this type of data is extremely labor-intensive, time-consuming, and costly. In this work, we propose a method for automated estimation of activity levels based on silhouettes segmented from video data, and subsequent extraction of higher order information from the silhouettes. By building a regression model from this higher order information, our system can automatically estimate elder activity levels.