PRE2018 4 Group8: Difference between revisions
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== Subject == | == Subject == | ||
Facial recognition (Just like Facebook) (happy/not happy) | Facial recognition (Just like Facebook) (happy/not happy) | ||
The use of Convolutional Neural Networks (CNNs) for the purposes of emotion recognition. | The use of Convolutional Neural Networks (CNNs) for the purposes of emotion recognition. | ||
== Sub-subjects == | |||
What is a possible application of our CNN emotion recognition technology? | |||
What is a suitable deep learning method to analyse dynamic facial expressions? | |||
What are the best features to use for facial expression analysis? | |||
== Plan == | == Plan == | ||
contains a subject (Problem statement and objectives), What do they require?, objectives, users, state-of-the-art, approach, planning, milestones, deliverables, who will do what, SotA: literature study, at least 25 relevant scientific papers and/or patents studied, summary on the wiki! | contains a subject (Problem statement and objectives), What do they require?, objectives, users, state-of-the-art, approach, planning, milestones, deliverables, who will do what, SotA: literature study, at least 25 relevant scientific papers and/or patents studied, summary on the wiki! | ||
Revision as of 11:40, 29 April 2019
Day 1
Members
| Name | Student ID | |
|---|---|---|
| Rik Hoekstra | 1262076 | r.hoekstra@student.tue.nl |
| Wietske Blijjenberg | 1025111 | |
| Kilian Cozijnsen | 1004704 | k.d.t.cozijnsen@student.tue.nl |
| Arthur Nijdam | 1000327 | c.e.nijdam@student.tue.nl |
| Selina Janssen | 1233328 | s.a.j.janssen@student.tue.nl |
Ideas
Surgery robots (Autonomous robots), Elderly care robots, New technology robot, Facial recognition (Just like Facebook) (happy/not happy)
Subject
Facial recognition (Just like Facebook) (happy/not happy)
The use of Convolutional Neural Networks (CNNs) for the purposes of emotion recognition.
Sub-subjects
What is a possible application of our CNN emotion recognition technology? What is a suitable deep learning method to analyse dynamic facial expressions? What are the best features to use for facial expression analysis?
Plan
contains a subject (Problem statement and objectives), What do they require?, objectives, users, state-of-the-art, approach, planning, milestones, deliverables, who will do what, SotA: literature study, at least 25 relevant scientific papers and/or patents studied, summary on the wiki!
Interesting persons
Emilia Barakova
weriak@iti.uio.no
Sources
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8039024
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=956083
https://link.springer.com/content/pdf/10.1007%2Fs00521-018-3358-8.pdf
https://link.springer.com/content/pdf/10.1007%2F978-94-007-3892-8.pdf
https://ieeexplore.ieee.org/abstract/document/1556608
https://pdfs.semanticscholar.org/e97f/4151b67e0569df7e54063d7c198c911edbdc.pdf
Bayesian face recognition https://www.sciencedirect.com/science/article/pii/S003132039900179X
Kalman filters for emotion recognition:
https://link.springer.com/chapter/10.1007/978-3-642-24600-5_53: Kalman Filter-Based Facial Emotional Expression Recognition This article uses a 3D candide face model, that describes features of face movement, such as 'brow raiser' and they have selected the most important ones according to them. The joint probability describes the similarity between the image and the emotion described by the parameters of the Kalman filter of the emotional expression as described by the features, and it is maximised to find the emotion corresponding to the picture. The system is more effective than other Bayesian methods like Hidden Markov Models and Principle Component Analysis.
https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4658455: Kalman Filter Tracking for Facial Expression Recognition using Noticeable Feature Selection. This paper used conventional CNNs to recognise the facial expression, but the tracking of the features was carried out with a Kalman Filter.
Facial recognition with the Google glass, for children with Autism Spectrum Disorder (ASD): https://humanfactors.jmir.org/2018/1/e1/ Second Version of Google Glass as a Wearable Socio-Affective Aid: Positive School Desirability, High Usability, and Theoretical Framework in a Sample of Children with Autism. See also https://www.youtube.com/watch?v=_kzfuXy1yMI for a demonstration of Stanford's autismglass.
But autistic children are not the only target group that has difficulty recognising emotions in others. This is also the case for elderly: https://www.tandfonline.com/doi/pdf/10.1080/00207450490270901. EMOTION RECOGNITION DEFICITS IN THE ELDERLY. This is problematic, as primary care facilities for the elderly try to care using their emotions, e.g. to cheer the elderly person up by smiling.
https://www.researchgate.net/profile/Antonio_Fernandez-Caballero/publication/278707087_Improvement_of_the_Elderly_Quality_of_Life_and_Care_through_Smart_Emotion_Regulation/links/562e0bc808ae518e34825f40/Improvement-of-the-Elderly-Quality-of-Life-and-Care-through-Smart-Emotion-Regulation.pdf. This paper proposes that the quality of life of the elderly improves if smart sensors that recognise their emotions are installed in their environment.