Microsoft Technology Licensing, LLC

Allison Light

David Benjamin Lee

Chunkit Jacky Chan

Stacia Scott

Doug Ricard

Catalin Alexandru Negrila

John Gabriel D'Angelo

Technologies for grouping images, and ranking the images and the groupings, based on entities shown in the images. Images may be grouped based on faces shown in the images. Different images with faces that indicate the same entity (e.g., Adam) may be automatically grouped together. Different images with faces that indicate the same multiple entities (e.g., the people in my family) may also be automatically grouped together. Such automatic grouping may be based on facial recognition technologies. Further, images and groups of images may be automatically ranked based on the faces shown and entities represented. Such rankings may also be influenced by adjacent data that indicates family and friends and the like, and that can be used to identify such entities in the images.

Image scoring and identification based on facial feature descriptors

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.

Creation of representative content based on facial analysis

Grouping and ranking images based on facial recognition data

Technologies for modifying a digital image to take on the appearance of an antique image. Such modifying is typically based on generating and rendering various effects that are blended with the input image, such as color transformation, simulating film grain, dust, fibers, tears, and vintage borders. Such effects may be rendered to various layers that are overlaid on a color transformed image resulting in what appears to be an antique image.

Saliency-preserving distinctive low-footprint photograph aging effects

Saliency-preserving distinctive low-footprint photograph aging effect

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Seattle, WA, United States of America

Allison Light