计算机科学 ›› 2018, Vol. 45 ›› Issue (8): 22-27.doi: 10.11896/j.issn.1002-137X.2018.08.005
毛峡1, 王岚1, 李建军1,2
MAO Xia1, WANG Lan1, LI Jian-jun1,2
摘要: 人体行为识别是计算机视觉和模式识别领域内一个重要的研究方向。人体行为的复杂性和不同人执行同一动作的差异性,使得行为识别仍然是一个具有挑战性的课题。采用新一代传感技术的RGB-D相机能够同时记录RGB图像和深度图像,并能够实时提取骨骼点信息。充分利用以上信息,成为行为识别领域的研究热点和突破点。文中提出了一种新的基于高斯加权金字塔式梯度方向直方图的RGB图像特征提取方法,并构建了一种多模特征融合的行为识别框架。在UTKinect-Action3D,MSR-Action 3D和Florence 3D Actions 3个数据库上对本研究所提特征和框架进行实验,结果表明,所提框架在3个行为数据库上的识别正确率分别达到了97.5%,93.1%,91.7%,从而证明了该行为识别框架的有效性。
中图分类号:
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