Patent Publication Number: US-2023161404-A1

Title: Gaze-based window adjustments

Description:
BACKGROUND 
     Computing devices allow interaction between users of different computing devices. For example, via a videoconferencing application, a user at one computing device can engage in video and audio communication with a user at another computing device. Computing devices also have the capability of allowing a user to simultaneously access multiple applications. For example, a first window may present a word processing application while a second window displays a video stream. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying drawings illustrate various examples of the principles described herein and are part of the specification. The illustrated examples are given merely for illustration, and do not limit the scope of the claims. 
         FIG.  1    is a diagram of a computing device for gaze-based window adjustments, according to an example. 
         FIG.  2    is a flowchart of a method for performing gaze-based window adjustments, according to an example. 
         FIG.  3    is a diagram of a computing device for gaze-based window adjustments, according to an example. 
         FIG.  4    is a diagram of a computing device for gaze-based window adjustments, according to an example. 
         FIG.  5    is a diagram of a controller for gaze-based window adjustments, according to an example. 
         FIG.  6    is a diagram of a computing device for gaze-based window adjustments, according to an example. 
         FIG.  7    depicts a non-transitory machine-readable storage medium for gaze-based window adjustments, according to an example. 
     
    
    
     Throughout the drawings, identical reference numbers designate similar, but not necessarily identical, elements. The figures are not necessarily to scale, and the size of some parts may be exaggerated to more clearly illustrate the example shown. Moreover, the drawings provide examples and/or implementations consistent with the description; however, the description is not limited to the examples and/or implementations provided in the drawings. 
     DETAILED DESCRIPTION 
     Computing devices are used by millions of people daily to carry out business, personal, and social operations and it is not uncommon for an individual to interact with multiple computing devices on a daily basis. Examples of computing devices include desktop computers, laptop computers, all-in-one devices, tablets, and gaming systems to name a few. In some cases, a user may simultaneously interact with different applications. For example, a first window may display a word processing application and another window may be display a video stream. In another example, a first window may display a first videoconferencing application and a second window may display a second videoconferencing application. Each of these windows and applications may utilize the same hardware components of the computing device. For example, a first videoconferencing application and a second videoconferencing application may access a camera and microphone of the computing device. However, simultaneous use of the different applications may lead to conflict, confusion, and/or inefficient use of the hardware components of the computing device. 
     For example, it may be that a video stream triggers a high refresh rate for a display device while a simultaneously executed word processing application does not require a high refresh rate. Accordingly, even when a user is focusing on the word processing application, a high refresh rate for the computing device may be triggered as the video stream is also active. This may result in increased power consumption and inefficient use of hardware resources of the computing device. 
     In another example, a user may have two videoconferencing applications open. A user may desire to switch from a first videoconference on the first videoconferencing application to a second videoconference on the second videoconferencing application. To do so, the user may need to manually disable the video and audio from the first video conferencing application and manually enable the video and audio for the second video conferencing application. 
     If video and audio settings are not switched, participants in the second videoconference may hear audio from the first videoconference, which may compromise the security of confidential information shared in the first videoconference. Similarly, if using external speakers, a user displaying both videoconferences may hear audio from both videoconferences, which may be overwhelming, confusing, and may reduce the efficacy of the either videoconference. Still further, allowing each videoconference application to both output and receive audio may lead to audio interference and/or distortion. 
     Still further, it may be that participants in either video conference will view the user switching their gaze between the videoconferences, which may be distracting and may overwhelm the computing device. 
     Manually switching the audio and video settings may be complex, time-consuming, and may negatively impact the efficacy of both video conferences. Moreover, manual switching may be prone to user error as a user may inadvertently maintain an audio/video connection to a first application as opposed to switching to a second application as they may have intended to do. 
     Accordingly, the specification provides a way to switch device settings including display, audio, and privacy settings between multiple applications by tracking the gaze of the user. That is, the application tracks the user&#39;s gaze or eye movement between two windows (which may be on different display devices). When the user is looking at a first window, the video of the second window, and in some cases the audio as well, may be adjusted (i.e., video blurred/disabled and audio muted), while the video and audio output from the first application is output. As a particular example, when a user switches focus from a first videoconference which is terminating, to a second videoconference which is just beginning, the video and audio settings may be automatically adjusted when the gaze region of the user switches to a window associated with the second videoconference. 
     Specifically, the specification describes a computing device. The computing device includes a gaze tracking device. The gaze tracking device identifies, from a captured image, a gaze region for a user viewing a display device coupled to the computing device. The gaze region indicates a location on the display device where the user is looking. The computing device also includes a controller. The controller determines a first window on the display device that is aligned with the gaze region. Based on a determination that the first window is aligned with the gaze region; the controller adjusts a video setting of a second window that is outside the gaze region. 
     In another example, the computing device includes a gaze tracking device that includes an artificial intelligence (AI) model. In this example, the gaze tracking device identifies, from a captured image of a user viewing a display device coupled to the computing device, a pupil position for the user and from the pupil position of the user, position data for a head of the user. The gaze tracking device identifies from the position data for the head of the user, a gaze region for the user. The computing device also includes a controller which identifies a first window of the display device. The controller determines whether the first window on the display device is aligned with the gaze region for the user. Responsive to a determination that the first window is aligned with the gaze region, the controller adjusts a setting of a second window that is outside the gaze region. 
     The specification also describes a non-transitory machine-readable storage medium encoded with instructions executable by a processor of a computing device. As used in the specification, the term “non-transitory” does not encompass transitory propagating signals. The instructions when executed by the processor, cause the processor to 1) capture an image of a user viewing a display device coupled to the computing device and 2) identify a gaze region associated with the image. As described above, the gaze region indicates a location on the display device where the user is looking. The instructions are also executable by the processor to cause the processor to 1) identify a first window boundary of the display device, 2) identify a second window boundary of the display device, and 3) compare the gaze region, first window boundary, and second window boundary to identify which of the first window boundary and second window boundary overlaps with the gaze region. The instructions, when executed by the processor, also cause the processor to adjust a setting of a second window, responsive to the first window boundary overlapping with the gaze region. 
     Turning now to the figures,  FIG.  1    is a diagram of a computing device  100  for gaze-based window  110  adjustments, according to an example. The computing device  100  may be of a variety of types including a desktop computer, a laptop computer, a tablet, or any of a variety of other computing devices  100 . As described above, at any point in time multiple windows  110 - 1 ,  110 - 2 , may be presented on a display device  102  coupled to the computing device  100 . The different windows  110  may correspond to different applications that are executing on the computing device  100 . As an example, a first window  110 - 1  may present a first videoconferencing application or session while a second window  110 - 2  presents a second videoconferencing application or a second session of the first videoconferencing application. At any given time, the user  112  may be focusing on a different one of the windows  110 . In the example depicted in  FIG.  1   , the user  112  is focusing on the first window  110 - 1  as indicated by the dashed lines. As described above, the computing device  100  can adjust the video and/or audio settings of the different windows  110  based on where the user  112  is focusing, or gazing. 
     For example, the gaze tracking device  104  may monitor the user&#39;s gazing direction. When the user  112  looks to the first window  110 - 1 , the controller  106  may switch the video and audio settings to de-emphasize the video and audio associated with the second window  110 - 2  while prioritizing the audio and video settings of the first window  110 - 1 . When the user  112  looks to the second window  110 - 2 , the controller  106  may switch the video and audio settings to de-emphasize the first window  110 - 1  while prioritizing the audio and video settings of the second window  110 - 2 . 
     Accordingly, the computing device  100  includes different components such as a gaze tracking device  104  and a controller  106 . Each of these components, as well as other components such as those depicted in  FIGS.  3 ,  4   , and  5  may include various hardware components, which may include a processor and memory. The processor may include the hardware architecture to retrieve executable code from the memory and execute the executable code. As specific examples, the controller as described herein may include computer readable storage medium, computer readable storage medium and a processor, an application specific integrated circuit (ASIC), a semiconductor-based microprocessor, a central processing unit (CPU), and a field-programmable gate array (FPGA), and/or other hardware device. 
     The memory may include a computer-readable storage medium, which computer-readable storage medium may contain, or store computer usable program code for use by or in connection with an instruction execution system, apparatus, or device. The memory may take many types of memory including volatile and non-volatile memory. For example, the memory may include Random Access Memory (RAM), Read Only Memory (ROM), optical memory disks, and magnetic disks, among others. The executable code may, when executed by the processor cause the processor to implement the functionality described herein. 
     The gaze tracking device  104  may identify, from a captured image  108 , a gaze region for a user  112  viewing a display device  102  coupled to the computing device  100 . The gaze region indicates a location on the display device  102  where the user  112  is looking. 
     A computing device  100  may include or be coupled to a capture device such as a camera. The camera may be positioned so as to capture an image of the user&#39;s face as they are looking at the display device  102 . The captured image  108  or stream of captured images  108  is passed to the gaze tracking device  104  which determines the gaze region of the user  112 . The gaze tracking device  104 , which may be a machine-learning gaze tracking device  104 , analyzes the captured image(s)  108  to determine various characteristics of the user position. For example, from the analysis of the captured image  108 , the gaze tracking device  104  may determine a yaw, pitch, and roll angle of the head of the user  112 . The gaze tracking device  104  may collect other data such as a distance between the user  112  and the display device  102 , a user presence in front of the display device  102 , a user focus in the field of view of the capture device, and a user eye state, i.e., whether the user&#39;s eyes are open or closed, or a combination thereof. In addition to this information, the gaze tracking device  104  may determine a gaze point for the user  112  in an x-direction, i.e., a horizontal direction and a gaze point for the user  112  in a y-direction, i.e., a vertical direction. 
     Gaze tracking may occur in a variety of ways. For example, a camera may project a pattern of near-infrared light on the pupils. In this example, the camera may take high-resolution images of the user&#39;s  112  eyes and the patterns. The gaze tracking device  104  may then determine the eyes position and gaze region based on the reflected patterns. 
     In some examples, the gaze tracking device  104  may be calibrated to allow the gaze tracking device  104  to recognize the location of the user&#39;s  112  eyes. In such an example, the computing device  100  may prompt the user  112  to make a sequence of eye movements such as a left-to-right movement and a top-to-bottom movement. 
     In an example, gaze tracking may include applying weights from an artificial intelligence model to the captured image  108 . For example, a training set of data may include thousands of images tagged by user viewing direction. In this example, the artificial intelligence model may be trained by viewing direction-tagged images. During training, weightings associated with characteristics of images are adjusted to fit the labeled output for the image. After the training is completed, these weighting factors are fixed for this model. Accordingly, once a captured image  108  is received, the weightings will be applied to the captured image  108  to determine the gaze region of the user  112 . 
     However obtained, the gaze region of the user  112  may be passed to a controller  106  which adjusts the settings of the computing device  100  based on the determined gaze region. Specifically, the controller  106  may identify a first window  110 - 1  on the display device  102  that is aligned with the identified gaze region. That is, the controller  106  may have access to metadata associated with the windows  110 - 1 ,  110 - 2 . The metadata indicates the window size and position. The controller  106  may determine whether the gaze region is aligned with either of these windows  110 - 1 ,  110 - 2  to determine whether the windows  110 - 1 ,  110 - 2  are the subject of focus of the user  112 . 
     As a particular example, a first window  110 - 1  may have x-y coordinates, indicating the boundary of the first window  110 - 1 . The controller  106  may receive an x-coordinate and y-coordinate for the gaze region of the user  112 . Responsive to the x and y coordinates for the gaze region falling within the coordinates of the first window  110 - 1 , the controller  106  may determine that the user  112  is actively focusing on the first window  110 - 1  and may adjust the settings of the first and/or second window  110  accordingly. As depicted in  FIG.  1   , the second window  110 - 2  may be on the display device  102  alongside the first window  110 - 1 . However, in other examples, such as that depicted in  FIG.  3   , the second window  110 - 2  may be on a second display device. 
     Based on a gaze region of the user  112  aligning with the first window  110 - 1 , the controller  106  may adjust a video setting of the second window  110 - 2  that is outside of the gaze region. For example, responsive to the gaze region of the user  112  aligning with the first window  110 - 1 , the controller  106  may blur a video stream of the user in the second window  110 - 2 . Doing so may prevent a participant of the video conference in the second window  110 - 2  from viewing the user  112  looking towards the first window  110 - 1  and not the second window  110 - 2 . 
     As a second example, the controller  106  may entirely disable a video stream of the user  112  in the second window  110 - 2  responsive to a determination that the first window  110 - 1  is aligned with the gaze region. As yet another example, the controller  106  may loop a pre-recorded video of the user  112  in a video stream of the second window  110 - 2 . That is, the controller  106  may pre-record a segment of video of the user  112  gazing in the direction of the second window  110 - 2  and may loop this pre-recorded video to participants in the videoconference associated with the second window  110 - 2 , such that participants in the videoconference associated with the second window  110 - 2  do not see the user looking away from the second window  110 - 2 . 
     In addition to adjusting the video settings of the second window  110 - 2 , the controller  106  may adjust an audio setting of the second window  110 - 2  that is outside of the gaze region, responsive to a determination that the user is gazing at the first window  110 - 1 . For example, the controller  106  may mute the audio passed to the videoconferencing application associated with the second window  110 - 2 . 
     In some examples, the controller  106  may make such adjustments after the user  112  has gazed at a particular window  110  for a threshold period of time. That is, a user  112  may look away from the first window  110 - 1  for a moment, for example to look at the time on the bottom of the display device  102 , after which the user&#39;s gaze returns to the first window  110 - 1 . Rather than altering and the re-altering the video and/or audio settings two times in that moment, the controller  106  may adjust the video settings after a threshold period of time. For example, the user gaze may switch from the second window  110 - 2  to the first window  110 - 1 . The controller  106  may adjust the video settings responsive to the first window  110 - 1  aligning with the gaze region for a threshold period of time, for example three seconds. Doing so may avoid switches that occur too frequently and that may be distracting to the user  112 . Moreover, frequent shifts, may overwhelm the processing resources of the computing device  100 . While particular reference is made to adjusting video and audio settings associated with videoconferencing applications, the controller  106  may adjust the settings of windows  110  associated with other, non-videoconferencing applications. 
     In addition to adjusting the settings of the computing device  100  based on the gaze region, the controller  106  may selectively activate and de-activate the gaze tracking device  104  itself. For example, it may be the case that one of the two windows  110  utilizes a capture device or an audio device while another does not. In such an example, it may not be necessary to adjust video and/or audio settings of the second window  110 - 2 . Accordingly, in this example, the gaze tracking device  104  may be activated responsive to metadata indicating that both the first window  110 - 1  and the second window  110 - 2  implement a stream from a capture device. When this occurs, the controller  106  may activate the gaze tracking device  104 . Still in this example, the controller  106  may de-activate the gaze tracking device  104  responsive to a count of windows  110  that implement the stream falling below two. Accordingly, the activation of the gaze tracking device  104  may be triggered by metadata indicating multiple windows  110  are activated that implement a stream from the capture device. 
     In other examples, the gaze tracking device  104  may be continually active. That is, the gaze tracking device  104  may continually determine a gaze region and the controller  106  may continually adjust settings based on the alignment of the gaze region with particular windows  110  on the computing device  100 . In yet another example, the gaze tracking device  104  may be manually activated. That is, the user  112  may activate the gaze tracking device  104  via a mechanical button or a user interface element. 
       FIG.  2    is a flowchart of a method  200  for performing gaze-based window  110  adjustments, according to an example. At step  201 , the method  200  includes capturing an image of a user  112  viewing a display device  102  coupled to a computing device  100 . That is, as described above, a capture device such as a camera may be directed towards a user  112  to capture the user  112  viewing the display device  102 . 
     At step  202 , the method  200  includes identifying a gaze region associated with the image. As described above, the gaze tracking device  104  may determine any number of characteristics of user  112  head position including a yaw, pitch, and roll of the head of the user  112 , an x-coordinate gaze point and a y-coordinate gaze point. In addition to this information, the gaze tracking device  104  may collect additional position data for the head of the user  112  including, but not limited to, a distance between the user  112  and the display device  102 , a user presence in front of the display device  102 , a user focus in the field of view of the capture device, and a user eye state, or a combination thereof. 
     At step  203 , the method  200  includes identifying a first window boundary of the display device  102 . In displaying the first window  110 - 1 , the computing device  100  may generate or access metadata which is indicative of a location and a position of the first window  110 - 1 . Such data may indicate coordinates of the boundary of the first window  110 - 1 . Similarly at step  204 , the method  200  includes identifying a second window boundary of the display device  102 . 
     At step  205 , the method  200  includes comparing the gaze region of the user  112  with the first window boundary and the second window boundary. This comparison allows the controller  106  to identify which window  110  the user  112  is focusing on. At step  206 , the method  200  includes adjusting a setting of the second window  110 - 2  responsive to the first window boundary overlapping with the gaze region of the user  112 . That is, when it is determined that the coordinates of the gaze region, i.e., the x-direction gaze point and the y-direction gaze point fall within the coordinate boundary of the first window  110 - 1 , the controller alters the settings of the second window  110 - 2 . This may include a variety of video-based adjustments including blurring a video stream of the user  112  in the second window  110 - 2 , disabling a video stream of the user  112  in the second window  110 - 2 , and/or providing a pre-recorded video loop of the user  112  in the second window  110 - 2 . As described above, such adjustments may occur after the user  112  gaze is aligned with the first window for a threshold period of time so as to avoid the distraction that may occur when windows  110  are switched between too frequently. As described above, in addition to adjusting video settings, the controller  106  may adjust an audio setting of the second window  110 - 2 , for example by muting the audio stream of the user  112  in the second window  110 - 2  that is outside the gaze region. 
       FIG.  3    is a diagram of a computing device  100  for gaze-based window adjustments, according to an example. As described above, in some examples the windows  110 - 1 ,  110 - 2  may be displayed on the same display device  102 . However, in other examples such as that depicted in  FIG.  3   , the second window  110 - 2  may be on a second display device  102 - 2  which is coupled to the computing device  100 , whereas the first window  110 - 1  is displayed on a first display device  102 - 1 . 
     Also as described above, in some examples the gaze tracking device  104  may be a machine-learning gaze tracking device  104  that compares the gaze region of the user  112  against a dynamic training set of data for which the gaze region of captured subjects is known. Accordingly, the gaze tracking device  104  may include an AI model  314  to assist in the determination of the gaze region from the captured image  108 . In an example, the AI model  314  may include a neural network, a deep neural network, an artificial neural network, or any other model that could be trained via machine learning. Based on the AI model  314 , the gaze tracking device  104  may identify which region of the computing device  100  the user  112  is looking at and transmit such information to the controller  106 . Specifically, based on the AI model  314 , the gaze tracking device  104  may identify, from a captured image of a user viewing a display device coupled to the computing device, a pupil position for the user. From the pupil position for the user, the gaze tracking device  104  may identify position data for a head of the user and ultimately may identify a gaze region for the user. 
     As described above, the controller  106  determines, a first window  110 - 1  on the display device  102  that is aligned with the gaze region for the user  112  and adjusts the settings of a second window  110 - 2  that is outside the gaze region responsive to the determination. 
     As described above, the settings of a particular window  110 , or an application associated with the window  110 , was adjusted. However, in some examples, responsive to the first window  110 - 1  overlapping with the gaze region, a device-wide setting of the computing device  100  may be adjusted based on metadata of the first window  110 - 1 . For example, the first window  110 - 1  may be associated with a word processing application and the second window  110 - 2  may be associated with a gaming application. For optimized performance, it may be desirable that a high refresh rate is implemented on the display device  102  when the gaming application is the subject of user focus. However, when the word processing application is activated or the subject of attention of the user  112 , the high refresh rate may be unnecessary and may overload the graphics display controller. Accordingly, responsive to an indication that the first window  110 - 1 , i.e., associated with the word processing application, is active, the controller  106  may decrease the refresh rate for the computing device  100 . By comparison, responsive to an indication that the second window  110 - 2 , i.e., associated with the gaming application, is active, the controller  106  may increase the refresh rate. While particular reference is made to one such setting that is adjusted based on a user  112  focusing on a particular window, any variety of settings may be similarly adjusted based on which window  110  the user  112  is looking at. Such adjustments of settings based on metadata associated with the active window  110  may result in improved and more efficient utilization of the resources of the computing device  100 . 
       FIG.  4    is a diagram of a computing device  100  for gaze-based window  110  adjustments, according to an example. As described above, the gaze tracking device  104  may receive a captured image  108  or sequence of captured images  108  of a user  112  looking at a display device  102  coupled to the computing device  100 . The gaze tracking device  104  determines where on the display device  102  the user  112  is looking. 
     Based on this and additional information, the controller  106  determines which window  110  the user  112  is looking at and adjusts the settings of the windows  110  and/or computing device  100  accordingly. 
     In an example, the additional information or input received at the controller  106  includes first window position information  416 - 1  and second window position information  416 - 2 . That is, applications, or the computing device  100  itself, may include metadata indicating a position and size of windows  110  on the display device  102 . This window position information  416  may be passed to the controller  106 . With the window boundaries identified and the gaze region of the user  112  identified, the controller  106  can determine which window  110  the user is looking at and a settings controller  420  of the controller  106  may pass the settings  422  for the windows  110  and/or computing device  100 . In one example, the settings controller  420  is an application programming interface associated with video, audio, or other aspects of the windows  110  and/or computing device  100 . 
     As described above, in some examples, the gaze tracking device  104  is activated based on whether or not the multiple windows  110  are active and whether or not they rely on video and audio components. Accordingly, the controller  106  may receive active window information  418 . This information may indicate 1) whether a second window  110 - 2  is active and 2) whether the second window  110 - 2  relies on audio and/or video stream. As described, this example pertains to a scenario where the gaze tracking device  104  is selectively activated. In other examples, the gaze tracking device  104  may be continually active or manually activated based on user  112  input. 
       FIG.  5    is a diagram of a controller  106  for gaze-based window  110  adjustments, according to an example. As described above, the controller  106  receives as input  1 ) a gaze tracking device output  524 , which is indicative of a gaze region  528  of the user  112 ,  2 ) window activation information  418  which is indicative of whether a second window  110 - 2  that implements audio and or video output is active, and 3) window position information  416  which is indicative of a location and size of different windows  110  that may be active. From this information, the controller  106  may execute a variety of operations. 
     For example, from the gaze tracking device output  524 , the controller may determine a gaze region  528 , which may include an x-coordinate gaze point and a y-coordinate gaze point. From this gaze region  528  information and the window position information  416 , the controller may determine a window identity  532  of the window  110  that the user  112  is looking at. This may be performed as described above. 
     The controller  106  may determine the active window identity  534 , that is the window  110  with video and audio settings activated. Based on this determination, the controller  106  may submit a change request  538  to the settings controller  420 . The change request  538  provides information to the settings controller  420  to establish the settings  422  such that the video and/or audio settings of the inactive window are disabled and/or muted. Note that the change request  538  and determination of the active window identity  534  are iterative and continuous to determine which of the windows  110  should be activated/deactivated. 
     In addition to this information, additional gaze tracking device output  524  information may be implemented in other ways. For example, the gaze tracking device  104  may output head status  526  information which may include the yaw, pitch, and roll of the head of the user  112 . Based on this information, the controller  106  may generate a window preload request  536 . For example, a user, administrator, or the computing device  100  may set a threshold gaze time of 500 milliseconds, which threshold gaze time refers to an amount of time for a gaze region to be towards a window  110  before switching settings. However, the computing device  100  may take 800 milliseconds to process the image data to identify a changed gaze region and adjust corresponding settings. Accordingly, the head status  526  information may provide a prediction that a gaze change is forthcoming such that this lag may be reduced. That is, a user  112  head may be tilted to one side indicative that although the user  112  is looking at the second window  110 - 2 , they are about to switch to look at the first window  110 - 1 . This may indicate a forthcoming switching of the user gaze from the second window  110 - 2  to the first window  110 - 1 . In this example, the controller  106  may pre-load the window  110 , i.e., by generating a command to switch, but may wait to switch until the gaze region  528  information confirms the change in gaze. 
     As described, the gaze tracking device  104  may collect additional position data for the head of the user  112 . In some examples, this additional position data may be user status  530  data and may include a distance between the user  112  and the display device  102 , a user presence in front of the display device  102 , a user focus in the field of view of the capture device, and a user eye state, or a combination thereof. Such information may be used to alter any adjustment to the setting  422 . For example, the user status  530  information may be used to prevent a switch. For example, gaze point  528  information may dictate that a switch should be made because the user is not looking at a first window  110 - 1 . However, it may be the case that the users  112  eyes are closed while they are still paying attention. Accordingly in this example, the user status  530  information may be used to prevent a setting change that otherwise would have occurred. 
     As another example, the user status  530  information may indicate that the user  112  is sitting beyond a threshold distance away from the computing device  100 , this threshold distance being a distance beyond which gaze tracking is unreliable. In this example, the user status  530  information may prevent a gaze-based switch which may have otherwise occurred. Accordingly, in this example, the user status  530  may authorize or prevent a change request  538  based on the additional position data. 
       FIG.  6    is a diagram of a computing device  100  for gaze-based window adjustments, according to an example. In addition to those components previously described, the computing device  100  of  FIG.  6    includes additional components. For example, the computing device  100  may include the capture device  642  to capture the image of the user  112  viewing the display device  102 . As described above, the capture device  642  may be a camera that is integrated with, or attached to, the display device  102  and is directed to face the user  112 . 
     The computing device  100  may also include a microphone  644 . In this example, responsive to a determination that the first window  110 - 1  is aligned with the gaze region, the controller  106  may disable a microphone output in a stream of the second window  110 - 2 . This microphone  644  may capture audio of the user  112  as they are engaging in a videoconference in the first window  110 - 1 , or audio from the speakers of the computing device  100 , which audio from the speakers may be from other participants in the videoconference in the first window  110 - 1 . In either case, it may be desirable to prevent this audio output from being transmitted as an audio stream to the second window  110 - 2 , for privacy and/or security reasons as well as to prevent audio interference. Accordingly, the controller  106  may disable the microphone  644  for use by the application of the second window  110 - 2 . 
       FIG.  7    depicts a non-transitory machine-readable storage medium  746  for gaze-based window adjustments, according to an example. As used in the specification, the term “non-transitory” does not encompass transitory propagating signals. To achieve its desired functionality, a computing device  100  includes various hardware components. Specifically, a computing device  100  includes a processor and a machine-readable storage medium  746 . The machine-readable storage medium  746  is communicatively coupled to the processor. The machine-readable storage medium  746  includes a number of instructions  748 ,  750 ,  752 ,  754 ,  756  for performing a designated function. The machine-readable storage medium  746  causes the processor to execute the designated function of the instructions  748 ,  750 ,  752 ,  754 ,  756 . The machine-readable storage medium  746  can store data, programs, instructions, or any other machine-readable data that can be utilized to operate the computing device  100 . Machine-readable storage medium  746  can store computer readable instructions that the processor of the computing device  100  can process, or execute. The machine-readable storage medium  746  can be an electronic, magnetic, optical, or other physical storage device that contains or stores executable instructions. Machine-readable storage medium  746  may be, for example, Random Access Memory (RAM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a storage device, an optical disc, etc. The machine-readable storage medium  746  may be a non-transitory machine-readable storage medium  746 . 
     Referring to  FIG.  7   , image capture instructions  748 , when executed by the processor, cause the processor to, capture an image of a user  112  viewing a display device  102  coupled to a computing device  100 . Identify gaze region instructions  750 , when executed by the processor, may cause the processor to identify a gaze region associated with the image. The gaze region indicates a location on the display device  102  where the user  112  is looking. Identify display region instructions  752 , when executed by the processor, may cause the processor to, identify a first window boundary of the display device  102  and identify a second window boundary of the display device  102 . Compare regions instructions  754 , when executed by the processor, may cause the processor to compare the gaze region, first window boundary, and second window boundary to identify which of the first window and the second window overlap with the gaze region. Adjust settings instructions  756 , when executed by the processor, may cause the processor to adjust a setting of the second window  110 - 2 , responsive to the first window boundary overlapping with the gaze region.