Music and Dance College of Xinyang Normal University, Xinyang, Henan 464000, China.
J Environ Public Health. 2022 Jul 19;2022:1568930. doi: 10.1155/2022/1568930. eCollection 2022.
Fine motion recognition is a challenging topic in computer vision, and it has been a trendy research direction in recent years. This study combines motion recognition technology with dance movements and the problems such as the high complexity of dance movements and fully considers the human body's self-occlusion. The excellent motion recognition content in the dance field was studied and analyzed. A compelling feature extraction method was proposed for the dance video dataset, segmented video, and accumulated edge feature operation. By extracting directional gradient histogram features, a set of directional gradient histogram feature vectors is used to characterize the shape features of the dance video movements. A dance movement recognition method is adopted based on the fusion direction gradient histogram feature, optical flow direction histogram feature, and audio signature feature. Three components are combined for dance movement recognition by a multicore learning method. Experimental results show that the cumulative edge feature algorithm proposed in this study outperforms traditional models in the recognition results of HOG features extracted from images. After adding edge features, the description of the dance movement shape is more effective. The algorithm can guarantee a specific recognition rate of complex dance movements. The results also verify the effectiveness of the movement recognition algorithm in this study for dance movement recognition.
精细动作识别是计算机视觉中的一个具有挑战性的课题，近年来已成为一个热门的研究方向。本研究将动作识别技术与舞蹈动作相结合，并充分考虑到舞蹈动作的高度复杂性和人体自身遮挡的问题。研究和分析了舞蹈领域中优秀的动作识别内容。针对舞蹈视频数据集、分割视频和累积边缘特征操作，提出了一种引人注目的特征提取方法。通过提取方向梯度直方图特征，使用一组方向梯度直方图特征向量来描述舞蹈视频动作的形状特征。采用基于融合方向梯度直方图特征、光流方向直方图特征和音频签名特征的舞蹈动作识别方法。通过多核学习方法，将三个分量结合起来进行舞蹈动作识别。实验结果表明，与传统模型相比，本文提出的累积边缘特征算法在从图像中提取 HOG 特征的识别结果上表现更好。添加边缘特征后，对舞蹈动作形状的描述更加有效。该算法可以保证对复杂舞蹈动作的特定识别率。研究结果还验证了本文所提出的动作识别算法在舞蹈动作识别中的有效性。
