Projector Image Warping for User Pose Adaptation
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Solution Overview
Problem
Existing automated assistant systems fail to dynamically adapt images projected by projectors based on the pose of users within an environment, leading to inconsistent user experiences due to perspective changes, especially for users with limited dexterity or those viewing from non-perpendicular angles.
Innovation Solution
Implementing a method where an automated assistant identifies active users and dynamically transforms base images using pose data from sensors, applying linear transformations such as rotation, scaling, and skew adjustments to maintain a consistent appearance of projected images across varying user positions and orientations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If base images are projected without dynamic transformation, then device complexity is reduced, but user experience consistency deteriorates due to perspective changes
Solution Approach 1:
The system dynamically transforms base images based on real-time detection of user pose parameters (position, orientation, gaze direction). The image transformation is continuously adjusted as the user moves, ensuring the projected image maintains consistent appearance from the user's perspective regardless of their position or orientation relative to the projection surface.
Solution Approach 2:
The system introduces an intermediate processing stage between the base image and the projected image. A transformation component receives the base image and applies geometric transformations (rotation, scaling, skewing) based on detected user pose parameters, generating a transformed image that compensates for perspective distortion. This intermediary transformation layer resolves the contradiction by adding adaptability without requiring fundamental system redesign.
2Adaptability or versatility
If transformed images are generated and projected, then user experience consistency is improved, but data transmission requirements increase
Solution Approach 1:
The system performs preliminary actions by detecting user pose parameters and pre-calculating the necessary image transformation parameters before generating the transformed image. By determining the transformation matrix based on user position, orientation, and gaze direction in advance, the system optimizes data transmission by sending only the essential transformation parameters rather than pre-generating and transmitting multiple pre-transformed image variants.
Solution Approach 2:
The system changes parameters by transforming the base image according to detected user pose parameters (position coordinates, orientation angles, gaze direction). The transformation component applies geometric parameter changes (rotation angles, scaling factors, skew parameters) to generate the transformed image, allowing adaptive image delivery without increasing base data storage requirements.
3Adaptability or versatility
If dynamic image transformation is implemented, then user experience from multiple poses is improved, but processing time increases
Solution Approach 1:
The system performs preliminary detection of user pose parameters (position, orientation, gaze) and pre-calculates transformation parameters before actual image generation. By preparing the transformation matrix in advance based on detected user state, the system minimizes processing delays during image rendering while maintaining adaptability to user pose changes.
Solution Approach 2:
The system creates a transformed copy of the base image rather than generating entirely new images for different user poses. The transformation component applies geometric transformations to replicate the base image content in a transformed coordinate system that compensates for perspective distortion, reducing processing time compared to generating completely new images for each user position.
4Manufacturing precision
If projected images are optimized for perpendicular viewing, then image quality is maintained, but usability for users with limited dexterity deteriorates
Solution Approach 1:
The system applies local quality adaptation by detecting the specific user pose (position, orientation, gaze direction) and applying targeted geometric transformations to the image regions that are most affected by perspective distortion. The transformation component adjusts image parameters locally based on the user's viewing angle and position, ensuring high image quality for users with limited dexterity who may view from non-perpendicular angles, while maintaining overall image fidelity.
Data Source
AI summary
Implementations relate to dynamic adaptation of images for projection by a projector, based on one or more properties of user(s) that are in an environment with the projector. The projector can be associated with an automated assistant client of a client device. In some versions of those implementations, a pose of a user in the environment is determined and, based on the pose, a base image for projecting onto a surface is warped to generate a transformed image. The transformed image, when projected onto a surface and viewed from the pose of the user, mitigates perceived differences relative to the base image.