Static Image Animation Using AI Foreground-Background Rendering
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Solution Overview
Problem
Users experience wait times with static images during content provisioning, leading to confusion and a less immersive experience, which can deter future use of the service.
Innovation Solution
Utilizing trained machine learning models for foreground/background separation and inpainting/outpainting to generate immersive animated effects from static images, reducing compute and bandwidth requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If static images are provided during wait times, then compute expensive resources are reduced, but user experience becomes less immersive and may cause confusion
Solution Approach 1:
The patent applies dynamics by transforming static images into animated content during wait times. The system generates animated versions of static images using generative AI models, creating dynamic visual content that engages users without requiring excessive compute resources. The animation is generated once and cached, then served dynamically to multiple users, resolving the contradiction between providing engaging content and conserving compute resources.
Solution Approach 2:
The patent implements preliminary action by pre-generating animated content from static images before users need it. The system creates animated versions of images during off-peak times or in advance, stores them in a cache, and serves them when users encounter wait times. This eliminates the need to generate expensive animated content on-demand, reducing compute resource consumption while maintaining high user experience quality.
2Reliability
If specific content is generated for wait times, then user experience is improved, but bandwidth use and compute resources increase
Solution Approach 1:
The patent applies copying by creating animated versions of existing static images rather than generating entirely new content. The system takes existing static images, animates them using generative AI models, and serves these animated copies during wait times. This approach improves user experience while consuming fewer bandwidth and compute resources compared to creating original content, as the base content already exists and only requires transformation rather than full generation.
Solution Approach 2:
The patent implements universality by creating animated content that can serve multiple purposes and be reused across different wait time scenarios. Once animated content is generated from a static image, it can be served to multiple users experiencing wait times for different operations (content provisioning, resource allocation, etc.). This multi-functional animated content reduces overall bandwidth and compute resource consumption compared to generating separate content for each wait scenario.
3Quantity of substance
If a blank screen is displayed during wait times, then resource consumption is minimized, but user confusion increases as users may think the request is frozen
Solution Approach 1:
The patent applies the intermediary principle by introducing animated content as a mediator between the blank screen and the actual processed content. The animated content serves as an intermediate visual element that confirms to users their request has been received and is being processed, eliminating the confusion caused by blank screens. This intermediary animated content consumes minimal resources compared to full video or complex graphics while effectively communicating request status to users.
Data Source
AI summary
Approaches presented herein may be used to generate animated images using two-dimensional (2D) static images. An input image may be used to generate a first image corresponding to a foreground of the input image and at least a second image corresponding to a background of the input image. The second image may include an inpainted region based on a mask generated from the first image. The first and second images may be provided with configuration settings for rendering on a client device.