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Dynamic Image Context Evaluation and Prioritization in Cloud Disclosure Number: IPCOM000235642D
Publication Date: 2014-Mar-17
Document File: 2 page(s) / 109K

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A system and method for dynamic image context evaluation and prioritization in a remote repository [cloud] is disclosed.

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Dynamic Image Context Evaluation and Prioritization in Cloud

Disclosed is a system and method for dynamic image context evaluation and prioritization in a remote repository [cloud].

In an example scenario, multiple photographers take photographs of the same image. The photographer would like to access to the best image, but there is no easy way to compare similar photos taken by multiple users/cameras and dynamically select the best one. Cloud based image sharing is utilized to allow a user to select the best image based on context matching and user sharing preferences. This enables users dynamically to harness multiple cameras to get the best photo possible. A processing engine is utilized to match stored images and their context to

the user requested image context while applying filters such as smile detection, image focus, red eye detection, eyes opened or closed.

Dynamic sharing is enabled between different/multiple cameras owned by different users based on match of the photos context (i.e. 80% of the photo's context is the same - has same characteristics) and user preferences (define when, how and with who they want to share photos - restrictions, preferences, etc.) utilizing a cloud.

An example use case for this could include, when multiple photographers (i.e. at a wedding, conference, event) take the same group photograph where context of the photographs taken by multiple users match. The images are uploaded to a cloud space, perhaps associated with the event. All authorized photographers can view images matched to the context of their own and select the preferred image.

Photographers would benefit from being able to choose an image of the same context that may be less blurred, with better facial expressions etc. Other examples of context comparison extends beyond group or facial images to subjects such as landscapes, sporting events or subjects at a different point in time.

In an example where two photographers attend an event, photographer A captures image 1 and uploads image 1 to a cloud repository. Photographer B uploads image 2 to the same cloud repository. Context aware software determines that the images 1 and 2 are of the same context. Either photographer A or B can now access either image from the cloud based repository for their use.

For multiple people capturing images:

There is increased likelihood of obtaining a quality image.

A poor image captured by a user can be replaced by a better image from the sharing group and/or user th...