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Method of Augmented Reality Visualization of Seasonal Changes and Conditions

IP.com Disclosure Number: IPCOM000240013D
Publication Date: 2014-Dec-22
Document File: 2 page(s) / 26K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a method of using augmented reality glasses to visualize a site of interest, and in real time change parameters for season, weather, time of day, or other events that would change the view of the site. The user can then capture an image of the location in the altered state.

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Method of Augmented Reality Visualization of Seasonal Changes and Conditions

Seasonal changes can make viewing of sites much different within a given environment. For example, during August the color of the leaves is green, whereas during fall the color of the leaves become yellow, orange, red, and brown. People who are travelling during August might want a way to view the location during October.

A method is needed to enable a user to visualize the changes of current surroundings to reflect a change in season, weather, or other external events. This would allow travelers to visualize and enjoy the site of travel with the ability to change parameters such as seasonal conditions.

The novel contribution is software that enables users with augmented reality glasses to visualize a site of interest in real time and change parameters for season, weather, time of day, or other events that would change the view of the site. The software automatically changes the color appropriate real life objects, overlays additional objects, etc.

Based on a selected time/season parameter of any location, the software searches for sample images/photographs of the places and accordingly performs image analysis to understand the environment during that time. The software creates a probabilistic model of changes and the distribution of changes in the environment.

To implement the software, the user looks at the surrounding area with head mounted display. Through this, the user can manually change the season parameter. Based on the selected season parameter, the software searches for images captured in that location, and then performs contextual analysis of the identified images. The software extracts the image objects (e.g., building, vehicle, leaf, tree, flowers, etc.) as well as the colors of the objects. Accordingly, the software creates a pattern, such as 50% of the leaves change to red, 20 % to yellow, and 20% green, etc. T...