What is the difference between blinking and winking

Jaimes and Sebe [ 13 ] presented a general review of methods used in multimodal human—computer interactions. They also described the use of face image analysis and gaze tracking. Blinking itself can be the basis of various applications. Grauman et al. The visual analysis of a facial image is the most popular method also the oldest one for blinking detection. Such an image can be captured with a camera. The face shape in the first step and the eye region in the second are separated.

Since then, various methods have been used for blinking detection: statistical analysis [ 2 ], pupil detection in the image [ 18 ], or image comparison to the templates [ 10 ].

To make the image analysis independent of the external lighting conditions, infrared IR radiation is sometimes applied. Blinking can be detected in a simple way by using the eye tracking method. Eye tracking oculography is used in many fields of research and interaction applications. Singh and Singh [ 33 ] presented a review of eye tracking implementations related to multimodal interactions. A review of methods used in eye tracking is presented in [ 1 , 29 ].

Eye tracking also allows the recognition of eye blinking as part of the standard task, but the use of eye tracking only for such a purpose would be ineffective. Blinking can be also recognized with other techniques: the use of surface electromyography sEMG for the identification of appropriate muscle tension [ 5 ] or the use of electrooculography EOG [ 20 ]. On the other hand, multimodal interaction with which our problem is related is a wider issue. It touches the recognition of human activities during various types of interactions [ 7 , 24 , 25 ].

A review of various solutions with regard to many aspects and comparative analysis is not the purpose of our article. However, it is worth to refer our proposal to similar solutions.

We present such a concise comparison in the scope of the considered solutions in summary of this article. Eyesight is the most complex sense of humans. The eye ensures the reception of visual impressions; it is a complex instrument, but a very delicate one.

The eyelids upper and lower serve a very important protective function. During the normal functioning of the sense of sight, blinking ensures the appropriate wetting of the cornea of the eye through an even distribution of tears. At the same time, this mechanism causes the natural removal of fine impurities from the surface of the cornea. Under difficult ambient conditions, closing the eyelids protects against dust and other impurities.

The closing of the eyelids blocks in fact significantly reduces the amount of light during sleep. The physiology of the eye and the blinking mechanism have been well known for a long time and have been documented [ 9 , 16 , 30 , 36 ].

Mental and emotional activities affect the frequency of blinking. Talking and verbal engagement, as well as anger, excitement, stress, fear, and fatigue, can increase the frequency by several times. In contrast, reading or absorbing visual work the concentration of drivers, for example , and above all, working at the computer, reduces the frequency of blinking. Environmental factors have an independent influence. Low humidity, cigarette smoke, and pollution naturally stimulate the blinking mechanism to work more frequently.

A single blink can be divided into three phases: fast eyelid closing, closure state, relatively slow approximately two times slower than closing opening [ 20 ]. The full cycle of a single blink takes from ms to ms [ 32 ]. It is often assumed that a longer time of closing the eye approximately ms means micro-sleep and is most often associated with fatigue. The natural blink includes synchronously both the left and the right eye and is a physiological activity that does not require control, although humans can consciously extend the period between blinks.

Winking is the conscious closing of the eyelids: in a conscious way, we can close independently the left and the right eye and control the closing time.

For a certain group of people, winking with one eye can be very difficult. The work of the eyelids is controlled by a complex muscle system. Further, the oculi and the levator palpebrae superioris muscle are associated with the upper eyelid, and the inferior palpebral muscle is associated with the lower eyelid [ 20 ]. Such muscles can be identified using sEMG.

The expected solution requires the consideration of various aspects. On the one hand, we took into account the solutions reported in previous studies. On the other hand, we analyzed the physiological properties of the eyes and the versatility of the considered applications. Therefore, we propose the following assumptions for our solution of the blink and wink recognition:.

It should allow us to distinguish blinking from winking on the basis of the analyzed eye closure time. The simplest solution, known from past research, would be to use a set of cameras, implement an appropriate face recognition algorithm, separate the eye image, and finally, analyze the eye state. However, such a solution does not meet our assumptions, and under real conditions, it would be very difficult to implement and ineffective.

To simplify the issue, we concentrate on the wearable technology [ 6 ]. Placing the camera locally very close to the eye allows us to limit the image only to the image of the eye or its fragment. This solution allows us to simplify the complicated image analysis as much as possible. Additionally, we propose the use of IR radiation and IR cameras to limit the effect of external disturbing factors lighting conditions, pollution, etc.

The application of wearable technology should meet an additional requirement: the used sensor camera, etc. The images of closed and open eyes differ significantly. In the first case, we see the skin of closed eyelids, and in the second case, the pupil, iris, and sclera white of the eye.

Such an application of skin color recognition would be very interesting. However, a preliminary study has shown that the color analysis for the diagnosis of eye closure is very complicated.

We propose the determination of the state of the eye on the basis of the analysis of the light reflection in the eye image [ 8 ]. The light that falls on any surface also the surface of the human body is partially reflected [ 3 , 8 ].

We can distinguish between specular directional or diffused scattered reflection depending on the type of surface. The surface of the eyelid skin reflects in a diffused manner, and the eyeball reflects, primarily, directionally. To carry out the analyses irrespective of the external lighting conditions, we decided to use IR radiation instead of visible light.

The IR radiation reflected from the eyeball when the eye was open was clearly visible Fig. In this case, we observed a small but very bright point of reflection. The IR radiation reflected from the eyelid if the eye was closed did not create such a visible bright point of reflection Fig. Therefore, we could very easily determine the state of the eye only on the basis of the reflection analysis.

If a bright point of specular reflection was observed, the eye was open; if not, the eye was closed. Captured image of the left eye: a closed and b open. The horizontal line passing through the brightest pixel is marked. Brightness distribution in this line: c closed eye and d open eye. We implemented the algorithm for the analysis of the images recorded by the micro cameras in three steps:.

Determination of the point of light reflection in the image. In the first version of the method, we observed that most often, the point of reflection was represented as a group of bright, neighboring pixels. Therefore, we searched for a group of pixels by analyzing the brightness difference between neighboring pixels. We analyze images stored in 8 bits of gray scale - which allows considering levels of luminance from 0 black to white.

In the image of the eye Fig. If there are several such neighboring points, they form the considered group. If there is only one such point, among the neighboring points we choose those that have a luminance level by 1 degree lower. These points together with the brightest point form the considered group. For several bright groups, we selected the brightest one.

After conducting experiments on a set of eye images opened and closed , we simplified the method. We found it considerably easier and sufficiently effective to simply look for the brightest pixel in the eye image.

Additionally, because we did not have to search the entire image, we limited the search area. The excluded areas are marked crossed in Fig. Excluded area means an area where the camera does not record the reflection. It depends, simply, on the position of the camera and the IR diode.

We determined it experimentally. Determination of the brightness profile for the image. After the first step, we found the brightest point in the image.

Through this point, a horizontal line of one pixel width was analyzed. For each point on this line, the brightness of the image was determined.

Then, we generated a brightness profile as a graph based on the brightness level of each pixel from this line Fig. The 1-byte grayscale was used; therefore, for each point of the brightness profile, a line segment of up to pixels was obtained. Determination of the eye state.

In this step, we analyzed the local differences in the brightness profile. Starting from the maximum point of the profile, we found the largest decrease in the neighborhood, taking into account the local level differences. The graph for the diffused reflection Fig. In this case, the eye was closed. The graph of specular reflection Fig. In this case, the eye was open. The base of the triangle corresponds to the level of luminance beyond the highest decrease in the luminance value near maximum.

Typical decreases in the luminance value for diffuse are 5—10 of gray levels, for specular approx. The differences between the decreases are so large that any threshold in this range allows distinguishing the eye condition correctly. This is indicated in the figures: the dashed line means the decrease of luminance value by 50 in relation to the maximum.

The brightness profile was analyzed only to distinguish between two cases specular or diffused reflection rather than determine the reflection properties. Therefore, the analysis was simple and fast. The most important part of the algorithm determination of the eye state based on the brightness profile in horizontal line can be described in symbolic form as a pseudo code pidgin code as follows:. LBP l,i. For simplicity, the maximum difference in the levels of luminance is searched for pixels in the range of.

We analyzed the channels for the left and the right eye separately. In each channel, the eye closure signal was recorded and its duration t x was measured. To correctly distinguish between blinking and winking, we experimentally determined the longest time of natural blinking t 0 and the shortest time of intentional winking t 1.

The set of gestures for the left and the right eye is shown in Fig. We did not analyze cases when one eye was closed and the other was winking because doing so is difficult for many people. Therefore, on the basis of the duration t x , we propose a simple classification for recognizing eye gestures. This denotes a special case caused by, for example, external factors air blast, dust, etc.

Such a closing of the eye cannot be included as intentional winking. However, this eye gesture is the closest to natural blinking.

Such a situation corresponds to the BL 0 and BR 0 gestures. We analyzed these gestures separately because the durations for the left and right eyes were different. This state is interpreted as gesture W 1. Report copyright infringement. The owner of it will not be notified.

Only the user who asked this question will see who disagreed with this answer. Read more comments. Blinking is just when you close your eyes really quick, the way you do naturally to keep them wet. Winking is where you close one eye and its meant to be a flirty action. You wink at someone.

See a translation. English US Portuguese Brazil. We wink in person, in emails and in text messages. The Winking Face emoticon was approved as part of Unicode 6. The act of winking involves contracting the orbicularis oculi muscle, which receives signals from the facial motor nucleus.

Pop star and overall queen Rihanna shocked the world when it was discovered that she could not wink. Being able to wink with one eye but not the other is referred to as ocular dominance. How does ocular dominance differ from writing with a dominant hand or walking with a dominant foot?

The two are governed by different parts of the brain. Your ocular dominance is governed by the part of the brain that controls your field of vision.

Find an eye doctor and book an exam. A wink is just a wink, they say, but in reality that rarely is the case. A wink can be fun, teasing, flirty and — depending on the one doing or receiving the winking — unsettling. The meaning of a wink depends on the context, the surroundings and most of all, the two people involved.

A wink can be appreciated or inappropriate, depending on the circumstances, timing and the relationship between the person doing the winking and the one who is winked at.