# Automatic Micro-Expression Apex Frame Spotting using Local Binary Pattern from Six Intersection Planes

arXiv: https://arxiv.org/abs/2104.02149 · HTML: https://mlsanity.com/paper/2104.02149/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 20 references that are in the map.
- First posted on arXiv 5 Apr 2021.

## Builds on (most cited first, 3 of 3)

- [Towards Reading Hidden Emotions: A comparative Study of Spontaneous Micro-expression Spotting and Recognition Methods](https://mlsanity.com/paper/1511.00423/) (2015)
- [Less is More: Micro-expression Recognition from Video using Apex Frame](https://mlsanity.com/paper/1606.01721/) (2016)
- [A Review on Facial Micro-Expressions Analysis: Datasets, Features and Metrics](https://mlsanity.com/paper/1805.02397/) (2018)

## Built on by (most cited first, 1 of 1)

- [COVID-19 Diagnosis: ULGFBP-ResNet51 approach on the CT and the Chest X-ray Images Classification](https://mlsanity.com/paper/2312.12876/) (2023)

## Abstract (arXiv)

Facial expressions are one of the most effective ways for non-verbal communications, which can be expressed as the Micro-Expression (ME) in the high-stake situations. The MEs are involuntary, rapid, and, subtle, and they can reveal real human intentions. However, their feature extraction is very challenging due to their low intensity and very short duration. Although Local Binary Pattern from Three Orthogonal Plane (LBP-TOP) feature extractor is useful for the ME analysis, it does not consider essential information. To address this problem, we propose a new feature extractor called Local Binary Pattern from Six Intersection Planes (LBP-SIPl). This method extracts LBP code on six intersection planes, and then it combines them. Results show that the proposed method has superior performance in apex frame spotting automatically in comparison with the relevant methods on the CASME database. Simulation results show that, using the proposed method, the apex frame has been spotted in 43% of subjects in the CASME database, automatically. Also, the mean absolute error of 1.76 is achieved, using our novel proposed method.