CAJ | 학술논문

该文利用飞行时间(Time-Of-Fligh, TOF)相机提供的距离图像，在运动历史图像的基础上提出一种基于多层运动历史图像的人体运动识别方法。计算距离轮廓序列的运动能量图作为整体运动信息，同时根据距离变化量，计算前向、后向的多层运动历史图像作为局部运动信息，共同组成多层运动历史图像。为了解决Hu矩对不连续或具有噪声的形状较为敏感的问题，引入R变换对每层运动历史图像进行特征提取，串联形成特征向量送入SVM进行分类识别。实验结果表明，该识别方法可以有效识别人体运动。
해문이용비행시간(Time-Of-Fligh, TOF)상궤제공적거리도상，재운동역사도상적기출상제출일충기우다층운동역사도상적인체운동식별방법。계산거리륜곽서렬적운동능량도작위정체운동신식，동시근거거리변화량，계산전향、후향적다층운동역사도상작위국부운동신식，공동조성다층운동역사도상。위료해결Hu구대불련속혹구유조성적형상교위민감적문제，인입R변환대매층운동역사도상진행특정제취，천련형성특정향량송입SVM진행분류식별。실험결과표명，해식별방법가이유효식별인체운동。
A new method extended from motion history image called Multi-Layered Mmotion History Images (MLMHI) is proposed to the representation and recognition of human activity using depth images provided by Time-Of-Fligh (TOF) camera. Firstly, the motion-energy image of the depth silhouettes is computed as the global motion information. Then, the forward-MLMHI and backward-MLMHI is computed as the local motion information based on the variable of depth. The global and local motion information constitute the MLMHI lastly. Since the Hu moments are sensitive to disjoint shapes and noise, R transform is employed to extract features from every layered-MHI and concatenated to form a feature vector. The feature vector is used as the input of Support Vector Machine (SVM) for recognition. Experimental results demonstrate the effectiveness of the proposed method.