Abstract: Described is a technique for optimization an image for facial detection. More specifically, described is a process of predicting the location of a face within an image and adjusting image settings based on at least a portion of the predicted location of the face. An image may be adjusted based on the characteristics of a metering region, which may be selected prior to performing facial detection. For example, the metering region may be a specified shape with dimensions equal to a certain percentage of the input image and placed at a specified location. The result of using such a metering region is that the image adjustments may be based on a portion of the face, and therefore, may be optimized for facial detection.

Abstract: Described is a technique for optimization an image for facial detection. More specifically, described is a process of predicting the location of a face within an image and adjusting image settings based on at least a portion of the predicted location of the face. An image may be adjusted based on the characteristics of a metering region, which may be selected prior to performing facial detection. For example, the metering region may be a specified shape with dimensions equal to a certain percentage of the input image and placed at a specified location. The result of using such a metering region is that the image adjustments may be based on a portion of the face, and therefore, may be optimized for facial detection.

Abstract: Described is a technique for optimization an image for facial detection. More specifically, described is a process of predicting the location of a face within an image and adjusting image settings based on at least a portion of the predicted location of the face. An image may be adjusted based on the characteristics of a metering region, which may be selected prior to performing facial detection. For example, the metering region may be a specified shape with dimensions equal to a certain percentage of the input image and placed at a specified location. The result of using such a metering region is that the image adjustments may be based on a portion of the face, and therefore, may be optimized for facial detection.

Abstract: Described is a technique for optimization an image for facial detection. More specifically, described is a process of predicting the location of a face within an image and adjusting image settings based on at least a portion of the predicted location of the face. An image may be adjusted based on the characteristics of a metering region, which may be selected prior to performing facial detection. For example, the metering region may be a specified shape with dimensions equal to a certain percentage of the input image and placed at a specified location. The result of using such a metering region is that the image adjustments may be based on a portion of the face, and therefore, may be optimized for facial detection.

Abstract: Described is a technique for optimization an image for facial detection. More specifically, described is a process of predicting the location of a face within an image and adjusting image settings based on at least a portion of the predicted location of the face. An image may be adjusted based on the characteristics of a metering region, which may be selected prior to performing facial detection. For example, the metering region may be a specified shape with dimensions equal to a certain percentage of the input image and placed at a specified location. The result of using such a metering region is that the image adjustments may be based on a portion of the face, and therefore, may be optimized for facial detection.

Abstract: Described is a technique for optimization an image for facial detection. More specifically, described is a process of predicting the location of a face within an image and adjusting image settings based on at least a portion of the predicted location of the face. An image may be adjusted based on the characteristics of a metering region, which may be selected prior to performing facial detection. For example, the metering region may be a specified shape with dimensions equal to a certain percentage of the input image and placed at a specified location. The result of using such a metering region is that the image adjustments may be based on a portion of the face, and therefore, may be optimized for facial detection.

Abstract: Described is a technique for optimization an image for facial detection. More specifically, described is a process of predicting the location of a face within an image and adjusting image settings based on at least a portion of the predicted location of the face. An image may be adjusted based on the characteristics of a metering region, which may be selected prior to performing facial detection. For example, the metering region may be a specified shape with dimensions equal to a certain percentage of the input image and placed at a specified location. The result of using such a metering region is that the image adjustments may be based on a portion of the face, and therefore, may be optimized for facial detection.

Abstract: Described is a technique for optimizing an image for facial detection. More specifically, described is a process of predicting the location of a face within an image and adjusting image settings based on at least a portion of the predicted location of the face. An image may be adjusted based on the characteristics of a metering region, which may be selected prior to performing facial detection. For example, the metering region may be a specified shape with dimensions equal to a certain percentage of the input image and placed at a specified location. The result of using such a metering region is that the image adjustments may be based on a portion of the face, and therefore, may be optimized for facial detection.

Abstract: The present disclosure includes systems and methods for creating and sharing inline commentary relating to media within an online community, for example, a social network. The inline commentary can be one or more types of media, for example, text, audio, image, video, URL link, etc. In some implementations, the systems and methods either receive media that is live or pre-recorded, permit viewing by users and receive selective added commentary by users inline. The systems and methods are configured to send one or more notifications regarding the commentary. In some implementations, the systems and methods are configured to receive responses by other users to the initial commentary provided by a particular user.