LBP with Six Intersection Points: Reducing Redundant Information in LBP-TOP for Micro-expression Recognition

By Yandan Wang, John See, Raphael Chung-Wei Phan, Yee-Hui Oh. Asian Conference on Computer Vision, 2014

316 citations recorded by the source corpus.

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Video-Based Facial Micro-Expression Analysis: A Survey of Datasets, Features and Algorithms (2021, methodology): “[44] proposed an LBP with six intersection points (LBP-SIP), which can delete the six intersections of repetitive coding.”
OFF-ApexNet on Micro-expression Recognition System (2018, background): “…several LBP variants are proposed and some of them are examined in micro-expression analysis, such as Local Binary Patterns with Six Intersection Points (LBP-SIP) [32], Spatiotemporal Local Binary Pattern with Integral Projection (STLBP-IP) [33], Completed Local Quantization Pattern (STCLQP) [34].”
Less is More: Micro-expression Recognition from Video using Apex Frame (2016, background): “In the recent few years, a number of research groups have attempted to improve the accuracy of microexpression recognition by designing a variety of feature extractors that can best capture the subtle facial changes [29, 12, 21], while a few other works [13, 15, 17] have sought out ways to reduce in”
Towards Reading Hidden Emotions: A Comparative Study of Spontaneous Micro-Expression Spotting and Recognition Methods (2015, unknown): “45%* Wang [57] 64.”