Dynamic control for data capture

Abstract

This application is directed to dynamic control for data capture. A device may comprise a capture logic module to receive at least one of biometric data from a biometric sensing module, context data from a context sensing module or content data from a content sensing module. The capture logic module may determine if a capture scenario exists based on at least one of the biometric data and context data. The determination may be weighted based on an operational mode. If a capture scenario is determined to exist, the capture logic module may then determine whether to capture data based on at least the content data. Captured data may be stored in a capture database in the device (e.g., along with enhanced metadata based on at least one of the biometric data, the context data or the content data). The device may also comprise a feedback database including feedback data.

1 .- 25 . (canceled) 
     
     
         26 . A mobile electronic device comprising:
 a housing;   a lens;   a button;   communication circuitry to wirelessly communicate;   one or more sensors to output sensor data representative of environment lighting, image framing, and image clarity;   a battery to power the mobile electronic device;   memory; and   processor logic circuitry to:
 recognize a person, 
 utilize a machine learning model to determine a capture moment based on the environment lighting, the image framing, the image clarity, and an excitement level of the environment, 
 trigger capture of an image in response to the determination of the capture moment, 
 determine feedback data based on user interaction with the image, the user interaction to include at least one of an image save operation or an image delete operation, and 
 train the machine learning model to determine a future capture moment based on the feedback data. 
   
     
     
         27 . The mobile electronic device of  claim 26 , wherein the processor logic circuitry is to trigger capture of a plurality of images in an interval in response to the determination of the capture moment. 
     
     
         28 . The mobile electronic device of  claim 27 , wherein the plurality of images are a video. 
     
     
         29 . The mobile electronic device of  claim 26 , wherein the communication circuitry is to wirelessly communicate the image to a display. 
     
     
         30 . The mobile electronic device of  claim 26 , wherein the sensor data is representative of color balance, and the processor logic circuitry is to determine the capture moment based on the color balance. 
     
     
         31 . The mobile electronic device of  claim 26 , wherein the processor logic circuitry is to determine the capture moment based on device load. 
     
     
         32 . The mobile electronic device of  claim 26 , wherein the user interaction is to include an image crop operation. 
     
     
         33 . The mobile electronic device of  claim 26 , wherein the processor logic circuitry is to tag the image with metadata indicative of a mood. 
     
     
         34 . The mobile electronic device of  claim 26 , wherein the processor logic circuitry is to determine the capture moment based on movement in the environment. 
     
     
         35 . A mobile electronic device comprising:
 a housing;   a lens;   a button;   communication circuitry to wirelessly communicate;   one or more sensors to output sensor data representative of environment lighting, image framing, and image clarity;   a battery to power the mobile electronic device;   memory; and   processor logic circuitry to:
 recognize a person, 
 utilize a machine learning model to determine a capture moment based on the environment lighting, the image framing, the image clarity, and an expression of the recognized person, 
 trigger retention of an image in response to the determination of the capture moment, 
 determine feedback data based on user interaction with the image, the user interaction to include at least one of an image save operation or an image delete operation, and 
 train the machine learning model to determine a future capture moment based on the feedback data. 
   
     
     
         36 . The mobile electronic device of  claim 35 , wherein the expression is a gesture. 
     
     
         37 . The mobile electronic device of  claim 35 , wherein the user interaction is to include an image crop operation. 
     
     
         38 . The mobile electronic device of  claim 35 , wherein the processor logic circuitry is to tag the image with metadata indicative of a mood. 
     
     
         39 . The mobile electronic device of  claim 35 , wherein the processor logic circuitry is to determine the capture moment based on movement in the environment. 
     
     
         40 . The mobile electronic device of  claim 35 , wherein the processor logic circuitry is to trigger retention of a plurality of images in an interval in response to the determination of the capture moment. 
     
     
         41 . The mobile electronic device of  claim 40 , wherein the plurality of images are a video. 
     
     
         42 . The mobile electronic device of  claim 35 , wherein the communication circuitry is to wirelessly communicate the image to a display. 
     
     
         43 . The mobile electronic device of  claim 35 , wherein the sensor data is representative of color balance, and the processor logic circuitry is to determine the capture moment based on the color balance. 
     
     
         44 . The mobile electronic device of  claim 35 , wherein the processor logic circuitry is to determine the capture moment based on process load. 
     
     
         45 . A mobile electronic device comprising:
 a housing;   a lens;   a button;   means for sending wireless communications;   means for sensing, the sensing means to output data representative of environment lighting, image framing, and image clarity;   means for powering the mobile electronic device;   memory; and   means for processing to:
 recognize a person, 
 utilize a machine learning model to determine a capture moment based on the environment lighting, the image framing, the image clarity, and an excitement level of the environment, 
 trigger capture of an image in response to the determination of the capture moment, 
 determine feedback data based on user interaction with the image, the user interaction to include at least one of an image save operation or an image delete operation, and 
 train the machine learning model to determine a future capture moment based on the feedback data. 
   
     
     
         46 . The mobile electronic device of  claim 45 , wherein the processing means is to trigger capture of a plurality of images in response to the determination of the capture moment. 
     
     
         47 . The mobile electronic device of  claim 45 , wherein the processing means is to determine the capture moment based on device load. 
     
     
         47 . The mobile electronic device of  claim 45 , wherein the user interaction is to include an image crop operation. 
     
     
         48 . The mobile electronic device of  claim 45 , wherein the processing means is to tag the image with metadata indicative of a mood. 
     
     
         49 . The mobile electronic device of  claim 45 , wherein the processing means is to determine the capture moment based on movement in the environment. 
     
     
         50 . A mobile electronic device comprising:
 a housing;   a lens;   a button;   means for sending wireless communications;   means for sensing, the sensing means to output data representative of environment lighting, image framing, and image clarity;   means for powering the mobile electronic device;   memory; and   means for processing to:
 recognize a person, 
 utilize a machine learning model to determine a capture moment based on the environment lighting, the image framing, the image clarity, and an expression of the recognized person, 
 trigger retention of an image in response to the determination of the capture moment, 
 determine feedback data based on user interaction with the image, the user interaction to include at least one of an image save operation or an image delete operation, and 
 train the machine learning model to determine a future capture moment based on the feedback data. 
   
     
     
         51 . The mobile electronic device of  claim 50 , wherein the expression is a gesture. 
     
     
         52 . The mobile electronic device of  claim 50 , wherein the user interaction is to include an image crop operation. 
     
     
         53 . The mobile electronic device of  claim 50 , wherein the processing means is to tag the image with metadata indicative of a mood. 
     
     
         54 . The mobile electronic device of  claim 50 , wherein the processing means is to determine the capture moment based on movement in the environment. 
     
     
         55 . The mobile electronic device of  claim 50 , wherein the processing means is to trigger retention of a plurality of images in response to the determination of the capture moment. 
     
     
         56 . The mobile electronic device of  claim 50 , wherein the processing means is to determine the capture moment based on device load.