Objective Classes for Micro-Facial Expression Recognition

Micro-expressions are brief spontaneous facial expressions that appear on a face when a person conceals an emotion, making them different to normal facial expressions in subtlety and duration. Currently, emotion classes within the CASME II dataset are based on Action Units and self-reports, creating conflicts during machine learning training. We will show that classifying expressions using Action Units, instead of predicted emotion, removes the potential bias of human reporting. The proposed classes are tested using LBP-TOP, HOOF and HOG 3D feature descriptors. The experiments are evaluated on two benchmark FACS coded datasets: CASME II and SAMM. The best result achieves 86.35\% accuracy when classifying the proposed 5 classes on CASME II using HOG 3D, outperforming the result of the state-of-the-art 5-class emotional-based classification in CASME II. Results indicate that classification based on Action Units provides an objective method to improve micro-expression recognition.Comment: 11 pages, 4 figures and 5 tables. This paper will be submitted for journal revie

Facial Behavioral Analysis: A Case Study in Deception Detection

YesThe objective of every wind energy producer is to reduce operational costs associated to the production as a way to increase profits. One other issue that must be looked carefully is the equipment maintenance. Increase the availability of wind turbines by reducing the downtime associated to failures is a good strategy to achieve the main goal of increase profits. As a way to help in the definition of the best maintenance strategies, condition monitoring systems (CMS) have an important role to play. Informatics tools to make the condition monitoring of the wind turbines were developed and are now being installed as a way to help producers reducing the operational costs. There are a lot of developed systems to do the monitoring of a wind turbine or the whole wind park, in this paper will be made an overview of the most important systems

A database for facial behavioural analysis

NoThere is substantial interest in detection of human behaviour that may reveal people with deliberate malicious intent, who are engaging in deceit. Technology exists that is able to detect changes in facial patterns of movement and thermal signatures on the face. However, there is data deficiency in the research community for further study. Therefore this project aims to overcome the data deficiency in psychology study and algorithms development. A within-subjects design experiment was conducted, using immigration as a scenario for investigate participants in control and experimental conditions. A random sample of 32 volunteers were recruited, their age group is within 18 - 33. The study design required participants to answer questions on two topics, one as themselves and one as a predefined character. Data regarding visible and thermal images of facial movement and behaviour were collected. A rich FACS-coded database with high quality thermal images was established. Finally, recommendations for development and subsequent implementation of the facial analysis technique were made