CAJ | 학술논문

采用指势进行人机交互，可充分发挥人类日常技能，摆脱常规输入设备束缚。实现自然的指势人机交互的关键是，如何从复杂的人机交互场景中有效提取指势用户对象，提出了基于时/空运动特征的指势用户对象识别新方法。基于多尺度小波变换在时/空域所具有的优异局部化特性，从复杂场景中提取前景运动对象，克服环境条件约束以及动态环境变化及先验假设等不足；基于多尺度小波变换的梯度积分图方法，获取稳定可靠的指势手部HOG特征，采用机器学习方法，对上述特征向量分类，并基于指势手与指势用户对象的空间关联性识别指势用户对象。通过实验对比，结果表明本文方法有效、可行。
채용지세진행인궤교호，가충분발휘인류일상기능，파탈상규수입설비속박。실현자연적지세인궤교호적관건시，여하종복잡적인궤교호장경중유효제취지세용호대상，제출료기우시/공운동특정적지세용호대상식별신방법。기우다척도소파변환재시/공역소구유적우이국부화특성，종복잡장경중제취전경운동대상，극복배경조건약속이급동태배경변화급선험가설등불족；기우다척도소파변환적제도적분도방법，획취은정가고적지세수부HOG특정，채용궤기학습방법，대상술특정향량분류，병기우지세수여지세용호대상적공간관련성식별지세용호대상。통과실험대비，결과표명본문방법유효、가행。
Human being daily skill can be exerted fully and bondage can be delivered efficiently in which people use ordinary equipment as an input way if pointing gesture is used for human-computer interaction (HCI ) .One of key problems is how to reliably recognize pointing user from HCI scene with cluttered background .A novel method has been developed based on spatio-temporal motion .According to multi-scale wavelet transform (MWT )with outstanding local characteristics both in spatial and temporal do-mains ,it is adopted to extract foreground motion subject from cluttered scene .Some disadvantages are overcome including restric-tions in environment conditions ,dynamic environment variation ,and a priori assumption .MWT based gradient integral graph is used to get some HOG feature vectors in pointing hand which are classified and learnt based on machine learning .Pointing user is recog-nized according to spatial relationship between pointing hand and its corresponding subject .Experimental results have been shown that the proposed method is efficient and viable .