CAJ | 학술논문

人类行为理解是实现“人本计算”模式的基础，其本质在于获取行为的语义，即由动作特征推导人体的行为，需要跨越两者之间的语义鸿沟；为此提出了环境上下文进行隐式建模的方法，并基于此提出了语义分层的行为推理框架，该框架使用了从模糊语义到确定语义的渐近式推理。根据知识将特征合理地分为多个层次，系统则根据当前状态去提取所需要的特征，推理当前可能的候选行为集；并由该候选行为集指导处理模块，更新特征集并进行新一轮的推理，反复迭代至推理完成。应用提出的环境建模方法和渐近推理框架可以有效地实现行为理解。使用隐式环境方法可以提高行为理解的准确率；渐近式推理框架可以避免传统推理方法无差别地提取所有特征，从而提升了推理效率。
인류행위리해시실현“인본계산”모식적기출，기본질재우획취행위적어의，즉유동작특정추도인체적행위，수요과월량자지간적어의홍구；위차제출료배경상하문진행은식건모적방법，병기우차제출료어의분층적행위추리광가，해광가사용료종모호어의도학정어의적점근식추리。근거지식장특정합리지분위다개층차，계통칙근거당전상태거제취소수요적특정，추리당전가능적후선행위집；병유해후선행위집지도처리모괴，경신특정집병진행신일륜적추리，반복질대지추리완성。응용제출적배경건모방법화점근추리광가가이유효지실현행위리해。사용은식배경방법가이제고행위리해적준학솔；점근식추리광가가이피면전통추리방법무차별지제취소유특정，종이제승료추리효솔。
Human activity recognition is the core of the implementation of human?centered computing ( HCC ) , whose nature is to acquire activities′semanteme. The basic problem is the semantic gap between observable actions and human activities. They should be bridged by environment context based inference. In this paper, a method is proposed to model the environment context implicitly. Further, a novel semanteme multilayered activity inference framework was presented, which divided the inferring process into 2 stages. One stage used to acquire fuzzy seman?teme and another one to acquire accurate semanteme. The feature set was divided into different subsets according to knowledge. The system extracts the corresponding features according to the current state and obtains the possible set of candidate activities that can instruct the system to update the current feature set. Update the features set and infer it, the process continues until the inference is completed. The modeling method and progressive inference frame?work proposed could handle the activity?recognition problem well. Implicitly modeling the environment context could improve the accuracy of activity recognition. The progressive framework can improve the efficiency by avoiding ex?tracting all features indistinguishably, whose validity was proven in the data set.