Recurrent Bidirectional Visual Human Pose Retrieval
Recurrent Bidirectional Visual Human Pose Retrieval
复制标题
循环双向视觉人体姿势检索
DOI：
10.1002/tee.22902
复制
发表时间：
2019
影响因子：
1
通讯作者：
Takuya Akashi
中科院分区：
文献类型：
--
作者：
Haitian Sun;Chao Zhang;Takuya Akashi
基于内容的图像检索技术是各种应用场景下必不可少的组成部分。在本文中，而不是由颜色，形状或纹理定义的视觉相似性，我们的目标是检索图像的视觉相似性定义的人的姿势。在我们的框架中，所有的姿势都来自图像，灵感来自三维（3D）人体姿势重建的最新发展。此外，为了使检索对重建错误更具鲁棒性，我们提出了一种循环双向相似性度量，称为循环最佳伙伴相似性（RBBS）。具体来说，我们把两个视觉姿势之间的相似性度量作为两个点向量之间的距离度量，每个点代表一个重建的3D人体姿势候选者。然后，我们通过查询的位移来重现相似性度量。作为证明，我们验证了RBBS在一维（1D）高斯情况下的有效性。在实验中，我们建立了一个原始数据集的检索任务。定性和定量的结果都表明了我们的框架的实用性;通过平均精度（MAP或mAP）评估的定量结果特别表明，RBBS与最具竞争力的替代方法相比提高了14.13%。2019年日本电气工程师协会出版社：John Wiley & Sons，Inc.
Content‐based image retrieval technique is an essential component under various application scenarios. In this paper, instead of visual similarity defined by colors, shapes, or textures, we aim to retrieve images with respect to the visual similarity defined by the human pose. In our framework, all the poses are derived from images, inspired by the recent development of three‐dimension (3D) human pose reconstruction. Furthermore, to make the retrieval more robust against reconstruction error, we propose a recurrent bidirectional similarity measure calledrecurrent best‐buddies similarity(RBBS). Specifically, we treat the similarity measure between two visual poses as a distance measure between two point vectors, with each point representing one of the reconstructed 3D human pose candidates. We then recur the similarity measure by the displacement of query. As a justification, we verify the validity of RBBS in a one dimension (1D) Gaussian situation. In experiments, we build an original dataset for the retrieval task. Both the qualitative and quantitative results show the usefulness of our framework; the quantitative results evaluated bymean average precision(MAP or mAP) especially demonstrate that RBBS is improved by 14.13% compared to the most competitive alternative methods. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.