3.0 Methodology
The figure 3.1 below shown the overall general workflow of the face emotion recognition system and OpenCV will be applied through the whole process.
Figure 3.1 General flow of the system
This project will mainly focus on face detection and feature extraction and only one webcam will be used and mounted on a laptop so that the image frame can be extracted out from the video. After we get the image, we will proceed to another stage which is face detection to detect the human face from that image frame.
3.1 Pre-processing
Since the entire image frame will not contain the same size of face, so skin detection will be applied in order to decrease the calculation time in finding the face. The skin colour will become as a requirements
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So in this step, we not only prepare eyes, nose and mouth data sets but also for the face to increase the accuracy in detecting face.
During this stage, Viola-Jones algorithm will be used to detect the face in OpenCV. This algorithm is based on Haar-like features and AdaBoost algorithm. In order to detect face and facial parts, four data sets which are human faces, eyes, nose and mouth were created. Firstly, those data sets will be calculated through Haar-like-features and then the features will be learned by AdaBoost algorithm. Later the classifiers will be applied in cascade structure in order to detect human face and facial parts. The database of face and facial parts will include positive images and negative images. Such as for face image database, 500 positive images (with face) and 500 negative images (without face) will be prepared same goes to others. All of the face and facial parts detection will be done in the skin pixel
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Both of the images will be combined and Figure 3.4.c shows the output. We can always get the two lips in angry, sadness, surprise, normal and disgust emotion. While for fear and happy emotion, we can distinguish then by saying the teeth often appears and there are more canny edge pixels will be detected in the mouth area. Figure 3.4 Process of detecting lips; a) binary output b) Canny edge detection output c) Combination of binary and canny edge
Besides mouth, the portion of eyes and eyebrows will be identified based on some requirement such as the eyes must locate at 60% above from bottom border of the face. The eyes and eyebrows region will further separate into left side and right side. The next step we need to consider on how to separate eye and eyebrow. Prewitt filter will be used to find the global maxima. The output should have two global maxima such as one global maxima is represented as eyebrows and another maxima is represented as eyes. The output has shown in Figure 3.5. Figure 3.5 The global maxima represents region of eyebrows and
The concept of face is referring to the socially approved self-image. It is about honor and shame belief and value systems. Facework is the verbal and nonverbal interactions we use in regards to our own social self-image and the social image of others.
A photon entering the skin will be scattered around by these particles therefore, be reflected from the skin in any direction with almost equal probability. This multiple scattering gives the skin its diffuse appearance. The reason for the white color of un-pigmented skin is that many of the skin particles have dimensions that are larger than, or as large as, the wavelengths of visible light. In that case the scattering efficiency does not vary strongly with wavelength. Had the skin particles been much smaller than the wavelengths of visible light, the skin would have appeared blue – just as light scattering by molecules in the air makes the sky appear blue.
There was a significant difference between the Black and White participants in the discrimination accuracy (d’) for Black faces. Black participants were significantly more accurate than White participants in recognizing Black faces. Black participants were found to be significantly better at recognizing Coloured faces than black faces and with coloured faces than white faces. Coloured participants were significantly better at recognizing Coloured faces than at recognizing Black faces. They were also significantly more accurate for White faces than they were for Black faces. White participants were worse at recognizing Black faces than at recognizing Coloured faces. They were also worse at recognizing Black faces than at recognizing White faces. Black participants were more confident with their responses for Black faces than they were for White faces , They were also more confident with their responses for Coloured faces than they were for White faces . White participants were more confident in their recognition responses for White faces as compared to Black faces. They were also more confident with their responses for White faces as compared to Coloured faces, these results show an own-race bias in confidence in the White participants
While communicating with another human being, one only has to examine the other’s face in order to comprehend what is being said on a much deeper level. It is said that up to 55 percent of a message’s meaning can be derived from facial expression (Subramani, 2010). These facial manipulations allow thoughts to be expressed in ways that are often difficult to articulate verbally, with the face demonstrating “the thoughts of the mind, and the feelings of the heart” (Singla). Many expressions are said to universal, particularly those showing happiness, sadness, fear, anger, disgust, and...
The most predominant feature of the human face is eyes. When talking to a person our eyes meet there eyes; the way that people identify each other is through eyes; eyes even have the power to communicate on its own. Eliezer identified people buy there eyes and knew their emotions through their eyes. “Across the aisle, a beautiful women with dark hair and dreamy eyes. I had
A person’s face is tremendously expressive when it comes to emotions, a person’s face is able to display a numerous amount of emotions worth almost a thousand words. And unlike some forms of nonverbal communication, facial expressions are universal worldwide. Facial expressions for feelings anger, disgust, fear, joy, sadness, surprise and many more are the same all around the world.
When Maxwell Smart first whipped out his shoe phone in 1965, everyone saw an act of pure movie magic. Back in the mid to late 1900s everybody had the same idea of the future. Everyone pictured the future as talking robots (Siri), computerized pocket-sized dictionaries (smart-phones), hovering devices (drones), and much more. Today, everyone thinks of these technologies as commonalities. Most of these current devices have a valuable impact, while few create debatable issues. The company NGI has a system that will revolutionize the field of biometric facial recognition. In the article titled Embracing Big Brother: How Facial Recognition Could Help Fight Crime, author Jim Stenman says, "The mission is to reduce terrorist and criminal activity by improving and expanding biometric identification as well as criminal history information s...
An individual’s ability to control and express their emotions is just as important as his/her ability to respond, understand, and interpret the emotions of others. The ability to do both of these things is emotional intelligence, which, it has been argued, is just as important if not more important than IQ (Cassady & Eissa, 2011). Emotional intelligence refers to one’s ability to perceive emotions, control them, and evaluate them. While some psychologists argue that it is innate, others claim that it is possible to learn and strengthen it. Academically, it has been referred to as social intelligence sub-set. This involves an individual’s ability to monitor their emotions and feelings, as well as those of others, and to differentiate them in a manner that allows the individuals to integrate them in their actions and thoughts (Cassady & Eissa, 2011).
Discuss the adaptive nature of facial and emotional recognition. Why is anger recognized more quickly, particularly on a man’s face as opposed to a woman’s?
1. The colours would be adjusted to this type of skin( a wide variety of darker colours )
[Jain, 2004] Jain, A.K.;Ross, A.;Prabhakar, S.;"An introduction to biometric recognition", Volume: 14 Issue: 1 Issue Date: Jan. 2004, on page(s): 4 - 20
In addition, emotions can be only transmitted by the human brain and cannot be programmed into a computer. One of the reasons is there are too many emotions to be described and they can be a mixture of feelings that it would be hard to put it into one category. Furthermore, the computer wouldn’t have the ability to know to what situation he should apply certain emotion. And different emotions can be applied to the same situation; it all depends on the experiences in our past. Emotions are personal and are different for every person and it would have to be different for every computer.
The face communicates emotions and how intensely they are felt. This can be used to manage expression, give feedback, and can vary by culture. An example of management, would be to give a blank expression in order to hide what you are feeling. An example of facial communication varying by culture is an Italian looking very angry when displeased but a Chinese person could be much more expressionless about
fact how we behave and what we feel is only the tip of the iceberg. I
Emotions are defined as "stereotypic patterns of the body, which are triggered by the central nervous system in response to distinct external environmental situations or to the recollection of memories related to such situations." (2) In other words, this means the emotions are the way the nervous system reacts to different situations one might find themselves in. In order to survive, emotional responses must be present. (2) "Whenever an emotion is triggered, a network of brain regions (traditionally referred to as the limbic system) generates a pattern of stereotypic outputs, which ultimately induce a biological response of the body." (2) These stereotypic outputs are what humans call emotions. They are predictable responses to certain situations, for instance when a person is in a sad situation, they will cry and feel depressed or if a person is in a happy situation, they will laugh and smile. These responses are because "specific circuits of the emotional motor system have evolved to both generate this stereotypic emotional facial response, as well as instantaneously recognize it when it occurs in somebody else." (2) This holds true for people in love, when you see someone in love you can tell because their face tells all.