Abstract: Technologies for analyzing various features detected in a face detected in an image. Such features may include at least the eyes, eyebrows, node, and mouth of a face. Such analyzing may include scoring aspects of these features. Such scores may be weighted. The analysis may be used to determine expressions and/or poses of the face, as well as indicate if the face is smiling, frowning, or neutral. An overall quality score for the face may also be determined and provided based on the aforementioned analysis as well as whether or not the face is near an edge of the image or cut-off in the image. Finally, a face signature may be determined that uniquely identifies the face, at least within the scope of the analyzed features. Such face signatures may be used to detect a similar face in other images.

Abstract: Technologies for analyzing various features detected in a face detected in an image. Such features may include at least the eyes, eyebrows, node, and mouth of a face. Such analyzing may include scoring aspects of these features. Such scores may be weighted. The analysis may be used to determine expressions and/or poses of the face, as well as indicate if the face is smiling, frowning, or neutral. An overall quality score for the face may also be determined and provided based on the aforementioned analysis as well as whether or not the face is near an edge of the image or cut-off in the image. Finally, a face signature may be determined that uniquely identifies the face, at least within the scope of the analyzed features. Such face signatures may be used to detect a similar face in other images.

Abstract: Technologies for analyzing various features detected in a face detected in an image. Such features may include at least the eyes, eyebrows, node, and mouth of a face. Such analyzing may include scoring aspects of these features. Such scores may be weighted. The analysis may be used to determine expressions and/or poses of the face, as well as indicate if the face is smiling, frowning, or neutral. An overall quality score for the face may also be determined and provided based on the aforementioned analysis as well as whether or not the face is near an edge of the image or cut-off in the image. Finally, a face signature may be determined that uniquely identifies the face, at least within the scope of the analyzed features. Such face signatures may be used to detect a similar face in other images.

Abstract: Technologies for analyzing various features detected in a face detected in an image. Such features may include at least the eyes, eyebrows, node, and mouth of a face. Such analyzing may include scoring aspects of these features. Such scores may be weighted. The analysis may be used to determine expressions and/or poses of the face, as well as indicate if the face is smiling, frowning, or neutral. An overall quality score for the face may also be determined and provided based on the aforementioned analysis as well as whether or not the face is near an edge of the image or cut-off in the image. Finally, a face signature may be determined that uniquely identifies the face, at least within the scope of the analyzed features. Such face signatures may be used to detect a similar face in other images.

Abstract: Technologies for analyzing various features detected in a face detected in an image. Such features may include at least the eyes, eyebrows, node, and mouth of a face. Such analyzing may include scoring aspects of these features. Such scores may be weighted. The analysis may be used to determine expressions and/or poses of the face, as well as indicate if the face is smiling, frowning, or neutral. An overall quality score for the face may also be determined and provided based on the aforementioned analysis as well as whether or not the face is near an edge of the image or cut-off in the image. Finally, a face signature may be determined that uniquely identifies the face, at least within the scope of the analyzed features. Such face signatures may be used to detect a similar face in other images.

Abstract: Technologies for selecting a representative subset of images from a set of images, the selecting based at least in part on rating the images in the set based on task, Image, and/or adjacent information. An Indication of the task may be embodied in a query provided by a user. The task may indicate the user's intended use of the subset of images. The set of images may be grouped into one or more clusters that are based on technical attributes of the images in the set, and/or technical attributes indicated by the task. Adjacent information may be obtained from sources that are generally unrelated or indirectly related to the images in the set.

Abstract: Technologies for analyzing various features detected in a face detected in an image. Such features may include at least the eyes, eyebrows, node, and mouth of a face. Such analyzing may include scoring aspects of these features. Such scores may be weighted. The analysis may be used to determine expressions and/or poses of the face, as well as indicate if the face is smiling, frowning, or neutral. An overall quality score for the face may also be determined and provided based on the aforementioned analysis as well as whether or not the face is near an edge of the image or cut-off in the image. Finally, a face signature may be determined that uniquely identifies the face, at least within the scope of the analyzed features. Such face signatures may be used to detect a similar face in other images.

Abstract: Asynchronous voice messaging is employed to enable individuals to send voice clips back and forth over a network. In at least some embodiments, the voice clips reside in the form of discrete, manageable objects that can be easily managed by the user. In addition, some embodiments described provide hand-free/eyes-free functionality that can permit a user to create and send (or receive and play) a voice message without having to physically enter an intended recipient's address or otherwise digitally manipulate the device over which the message is sent or received.

Abstract: The claimed subject matter is directed to the conversion of ordinary email data into calendar data. Specifically, the claimed subject matter provides a method and system of an electronic communication message system that performs the creation of calendar events in a personal calendar application from electronic communication text. One embodiment of the claimed subject matter is implemented as a method for creating an electronic calendar event from a selected portion of text from electronic communication message. An electronic communication message is displayed to a user. A user selected portion of the text comprising the electronic communication message is received as input. A scheduling composition dialog is actuated based on the user selected portion, and a calendar event is created in a personal calendar application for the selected portion of the electronic communication message.

Abstract: Asynchronous voice messaging is employed to enable individuals to send voice clips back and forth over a network. In at least some embodiments, the voice clips reside in the form of discrete, manageable objects that can be easily managed by the user. In addition, some embodiments described provide hand-free/eyes-free functionality that can permit a user to create and send (or receive and play) a voice message without having to physically enter an intended recipient's address or otherwise digitally manipulate the device over which the message is sent or received.