摘要
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。
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.
出处
《电子与信息学报》
EI
CSCD
北大核心
2014年第5期1139-1144,共6页
Journal of Electronics & Information Technology
基金
国家自然科学基金(61273237
61271121)
安徽省自然科学基金(11040606M149)资助课题
