Adobe, Inc.

Ram Prasad Purumala

Angad Kumar Gupta

Alok Kumar Singh

Manik Singhal

Dheeraj Kumar

Ankit Gulati

Nitish Singla

Navneet Kaur

Akhil Deshmukh

Geotag data embedded in a photograph is converted to a multilevel hierarchical place name tag, which is a new data structure. Higher hierarchy levels correspond to larger geographical regions. Lower hierarchy levels correspond to smaller geographical regions. The geotag data is used to locate the photograph on a map. A cluster of nearby photographs is defined and represented by a consolidated pin. The identification and quantity of clustered photographs depends on the relative locations of the photographs and the map zoom level. A consolidated pin label is defined based on which hierarchy levels, if any, have a common place name tags. In some cases the consolidated pin label includes only place name tags that are shared amongst all clustered photographs. In other cases the consolidated pin label includes a short list of mutually exclusive place name tags. The consolidated pin label is displayed on the map near the consolidated pin.

Labelling of aggregated geolocation tags in a digital mapping system

Systems and methods are disclosed for applying geo-tags to digital media items. In particular, in one or more embodiments, the disclosed systems and methods identify a plurality of digital media items lacking location information and group the plurality of digital media items into clusters based on one or more characteristics (e.g., time of capture). The systems and methods can modify the size and numbers of clusters of digital media items utilizing a clustering algorithm, clustering parameters, and a cluster adjustment control to approximate a location where the digital images were captured. Moreover, systems and methods provide a user interface for quickly and efficiently applying geo-tags to the clusters corresponding to the location.

Applying geo-tags to digital media captured without location information

A technique for selecting a representative image from a group of digital images includes extracting data representing an image of a face of a person from each image in the group using a face recognition algorithm, determining a score for each image based on one or more quality parameters that are satisfied for the respective image, and selecting the image having the highest score as the representative image for the group. The quality parameters may be based on any quantifiable characteristics of the data. Each of these quality parameters may be uniquely weighted, so as to define the relative importance of one parameter with respect to another. The score for determining the representative image of the group may be obtained by adding together the weights corresponding to each quality parameter that is satisfied for a given image. Once selected, the representative image may be displayed in a graphical user interface.

Representative image selection for image management using face recognition

Photograph organization based on facial recognition is described. In one or more embodiments, a photograph organization module obtains multiple photographs having images of faces and recognizes the faces in the multiple photographs. The module builds a population by attempting to distinguish individual persons among the faces in the multiple photographs, with each person of the population corresponding to a group of multiple groups. After a first pass through the faces, the population includes a number of duplicative persons. With a second pass, the photograph organization module reduces the number of duplicative persons in the population by merging two or more groups of the multiple groups to produce a reduced number of groups. The merging is performed based on comparisons of the faces corresponding to the two or more groups. The multiple photographs are organized based on the reduced number of groups. Organization can include tagging or displaying grouped photographs.

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Noida, India

Ram Prasad Purumala