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Augmented Reality Advertising at the Right Moment on the Right Surface of the Right Item Disclosure Number: IPCOM000257319D
Publication Date: 2019-Jan-31
Document File: 4 page(s) / 100K

Publishing Venue

The Prior Art Database

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Augmented Reality Advertising at the Right Moment on the Right Surface of the Right Item Augmented Reality (AR)-based advertising occurs through the insertion of advertisements (ads) into the visual space that the AR provides. Some of the ads are personalized to the user. However, a hyper-localized AR based advertisement wherein the delivery of the advertisement comprises creating an action on a hyper-local space, is not available. AR-based advertising does not currently fulfill all of a user’s needs. Desired capabilities for AR include, but are not limited to:

 Identify an object: for example, when a person sees a garment worn by someone else (or, in the mirror, a garment worn by self), the AR unit identifies it (“human wearing a garment”)

 Find the deviations of features (attributes) from usual of the objects (“the human looks clean”, “the garment looks dirty”)

 Find the undesirable states (“dirty”) and associate that with objects (“garment”)  Find associations of ads that handle “dirty” “garments”, and then deliver ads on

the AR that are relevant to handling dirty garments (e.g., detergent)  Overlay the delivery of the text/image (e.g., of detergent )on the garment, and

over time, show an altered (e.g., “cleaned up”) version of the garment; a method is needed to synthesize an image (using well-known image filtering mechanisms and a target color) and overlay it on the AR (e.g., on top of the physical actual garment)

Disclosed are a system and associated methods for advertising using augmented reality to advertise the right item on the right surface at the right moment. The novel system and method allow advertisers to specify attributes and actions of objects (e.g., “dirty garment” for advertising a detergent). Using external (not novel) modules, the system identifies the physical-world objects in the preview of the AR along with the attributes of the physical-world objects. The system compares the expected “ideal/perfect” objects with the seen physical-world objects, wherein the “perfect” objects are present at a backend database. The process includes identifying seen physical- world objects that are not sufficiently close in terms of one or more attributes (e.g., color, contour, shape, brightness etc.) to the “ideal/perfect” objects. The system uses back-end association mappings of these “non-perfect” attributes and objects with a given set of potential advertisements that address those “non-perfect” factors. The system ranking these advertisements using quantification of non-perfection (e.g., the number of non-matching attributes, the level of non-perfection of each attribute, the number of non-perfect attributes in an object etc.) and other given policies (such as

cutoff thresholds). It then choose from among these advertisements to deliver to the AR unit of the user, using external ad selection methodologies. Finally, the system delivers these advertisements by overlaying these on the appropriate surface (overlaying on the physical...