面向行为识别的人体空间协同运动结构特征表示与融合

针对人体执行动作时不同身体部位之间的协同关系，提出了基于人体空间协同运动结构特征的行为识别方法。首先度量人体不同部位对完成动作的贡献度，并将不同部位的贡献度转变为协同运动结构特征模型。然后利用模型无监督、自适应地对不同身体部位的运动特征进行约束。在此基础上借鉴跨媒体检索方法JFSSL对不同模态的特征进行特征选择与多模态特征融合。实验表明，所提方法在自建的行为数据库上明显提高了开放测试的识别率，且计算过程简便，易于实现。 

Structural feature representation and fusion of behavior recognition oriented human spatial cooperative motion

In view of the synergistic relationship among different parts of the body when human body performs actions, a behavior recognition method based on human body spatial cooperative motion structural features is proposed. Firstly, the contribution of different parts of the human body to the completion of the action is measured, and the contribution of different parts of the human body is transformed into a structural feature model of cooperative motion. Then, the model is used to constrain the motion characteristics of different parts of the body self-adaptively without supervision. On this basis, feature selection and multi-modal feature fusion are carried out using JFSSL, a cross-media retrieval method. The experiments show that the recognition rate of the open test is obviously improved by the proposed method on the self-built behavior database. At the same time, the calculation process of the method is simple and easy to implement.