Micro-expression recognition using local binary pattern from five intersecting planes

Micro-expression recognition using local binary pattern from five intersecting planes
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DOI:
10.1007/s11042-022-12360-x
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发表时间:
2022-03
影响因子:
3.6
通讯作者:
Jinsheng Wei;G. Lu;Jingjie Yan;Huaming Liu
Jinsheng Wei;G. Lu;Jingjie Yan;Huaming Liu
中科院分区:
计算机科学4区
文献类型:
--
作者:
Jinsheng Wei;G. Lu;Jingjie Yan;Huaming Liu

文献摘要

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微表情识别具有重要的研究价值和巨大的研究难度。三个正交平面的局部二值模式(LBP-TOP)是微表情识别中常用的有效特征。然而,LBP-TOP只提取了水平和垂直方向的动态纹理特征,没有考虑斜向的肌肉运动。本文研究了倾斜方向的特征,通过分析微表情视频中面部肌肉的运动方向,提出了一种新的面部表情特征--五个相交平面的局部二值模式(LBP-FIP)。LBP-FIP将所提出的八个顶点LBP(EVLBP)与从三个平面提取的LBP-TOP连接,其中EVLBP是从倾斜方向上的两个平面提取的。这样,在倾斜方向上的动态纹理特征被更直接地提取。在CASME II和SMIC数据库上,我们评估了所提出的特征和斜向特征的有效性。大量的实验证明,LBP-FIP比LBP-TOP提供了更有效的特征信息,并且提取的斜向特征对微表情识别具有区分性。同时,LBP-FIP与其他基于LBP的特征相比具有优势,并取得了令人满意的性能,特别是在CASME II上。
Micro-expression recognition has important research value and huge research difficulties. Local Binary Pattern from Three Orthogonal Planes (LBP-TOP) is a common and effective feature in micro-expression recognition. However, LBP-TOP only extracts the dynamic texture features in the horizontal and vertical directions and does not consider muscle movement in the oblique direction. In this paper, the feature in oblique directions is studied, and a new feature called Local Binary Pattern from Five Intersecting Planes (LBP-FIP) is proposed by analyzing the movement direction of facial muscles in the micro-expression video. LBP-FIP concatenates the proposed Eight Vertices LBP (EVLBP) with LBP-TOP extracted from three planes, where EVLBP is extracted from two planes in the oblique direction. In this way, the dynamic texture features in the oblique direction are extracted more directly. On the CASME II and SMIC database, we evaluated the proposed feature and the effectiveness of the features in the oblique direction. Extensive experiments prove that LBP-FIP provides more effective feature information than LBP-TOP, and extracting the features in oblique directions is discriminative for recognizing micro-expressions. Also, LBP-FIP has advantages comparing with other LBP based features and achieves satisfactory performance, especially on CASME II.