Augmented Reality Souvenir Image Morphing via Infrared Grid Correlation
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Solution Overview
Problem
Conventional souvenir photography in amusement parks lacks integrated augmented reality, only allowing secondary fictitious material to be added as a separate image segment, not seamlessly integrating with the guest's imagery.
Innovation Solution
A method and system that captures a digital image of a guest, invisible grid-strips a portion of the guest using infrared light, correlates the grid coordinates, selects and morphs a graphical image to match the guest's contours, and superimposes it onto the digital image, creating an integrated augmented reality souvenir.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional souvenir photography is used with separate augmented image segments, then the augmentation process is simple, but the integration quality is poor
Solution Approach 1:
The guest image is divided into multiple segments based on detected body parts or regions of interest. Each segment can be independently processed and augmented with relevant graphical elements, then reassembled to create the final integrated souvenir photograph. This segmentation allows complex augmentations to be managed through simpler, modular operations.
Solution Approach 2:
Multiple augmented image segments are merged and composite with the original guest image to create a seamless integrated souvenir photograph. The merging process involves aligning, blending, and compositing various augmented elements with the guest's actual appearance to achieve natural integration rather than separate overlays.
2Device complexity
If augmented reality imagery is added as separate segments, then the processing complexity is low, but the visual integration is insufficient
Solution Approach 1:
The system dynamically adjusts the positioning, scaling, and transformation of augmented graphical elements based on the detected guest image characteristics. This dynamic adaptation ensures that augmented elements naturally conform to the guest's body contours and pose, creating visually integrated results that appear reliable and authentic rather than artificially imposed.
Solution Approach 2:
Traditional mechanical image editing techniques are replaced with automated computer vision and machine learning algorithms that detect body parts, estimate three-dimensional geometry, and generate appropriate augmentations. This substitution reduces manual processing complexity while improving the reliability of visual integration through intelligent automated decision-making.
3Device complexity
If simple souvenir photography is used, then the equipment requirements are minimal, but the guest experience is ordinary
Solution Approach 1:
The souvenir photography system is designed with multi-functionality, capable of handling various guest scenarios, attraction contexts, and augmentation types through a single integrated platform. The system can detect different body parts, apply various graphical overlays, and adapt to different guest poses and environments, providing versatile enhanced experiences without requiring multiple specialized equipment sets.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach generates an augmented reality image of the guest that is seamlessly integrated with their body contours, enhancing the souvenir photography experience by creating a more immersive and memorable image.
Implementation Method 1
The grid-striping is drawn across contours of the portion of the guest by transmitted infrared light of an infrared light grid-stripe projector
Implementation Method 2
an infrared light camera sensing the invisible grid pattern
Data Source
AI summary
Photographic souvenir augmentation includes capturing a digital image of a guest at a location in an attraction and invisibly grid-striping of a portion of the guest based upon a two-dimensional grid. The augmentation additionally includes image sensing the grid-striped portion of the guest and correlating locations of the two-dimensional grid with locations of the grid-striped portion. The augmentation yet further includes selecting a graphical image and transforming the graphical image according to the correlation into a morphed graphical image. Finally, the augmentation includes superimposing the morphed graphical image onto the digital image of the guest and storing the digital image in association with an identifier for the guest.


