Timelapse Memory Reconstruction Using Multisensory AR/VR Triggers
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Solution Overview
Problem
Existing augmented and virtual reality technologies lack the ability to create immersive and contextual timelapse memory experiences that allow users to relive memories in a multisensory manner, failing to effectively capture and present data from various moments in time to recreate a contextual memory experience.
Innovation Solution
A networked computing environment that captures sensor data from various sources, including user devices and external sensors, to create timelapse memory experiences, which are then presented through augmented and virtual reality systems, using triggers to recreate multisensory environments for reliving memories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional AR/VR technologies are used, then virtual content can be presented, but the ability to create immersive timelapse memory experiences with multisensory data is lacking
Solution Approach 1:
The system segments memory experiences into discrete temporal snapshots captured at different time points, allowing each moment to be independently processed and reconstructed. This enables the timelapse functionality by dividing continuous memory into manageable temporal segments that can be selectively retrieved and presented.
Solution Approach 2:
Multiple layers of data are nested within the memory experience structure, including sensor data, contextual information, and virtual content representations. This nested architecture allows the system to preserve and reconstruct multisensory details while maintaining the temporal structure of the memory experience.
2Measurement precision
If sensor data from multiple sources is captured to create immersive experiences, then contextual accuracy improves, but system complexity increases
Solution Approach 1:
The system employs a universal data capture framework that can integrate multiple sensor types (visual, auditory, haptic, biosignal) through a common processing architecture. This multi-functional approach allows the system to handle diverse sensor data uniformly, improving contextual accuracy without proportionally increasing system complexity.
Solution Approach 2:
A centralized processing system acts as an intermediary between multiple sensor sources and the memory reconstruction process. This intermediary layer standardizes and contextualizes data from various sensors, managing complexity by creating a unified representation that can be consistently reconstructed across different scenarios.
3Measurement precision
If timelapse memory experiences are reconstructed with high fidelity, then immersion is improved, but the ability to share socially in real-time is limited
Solution Approach 1:
The system dynamically adjusts the level of detail and temporal resolution based on the sharing context. For social sharing, the system can provide summarized or highlight versions of memory experiences, while allowing high-fidelity reconstruction for personal viewing. This dynamic adaptation enables both high immersion quality and efficient social sharing.
Solution Approach 2:
Memory experiences are pre-processed and indexed with key moments and contextual metadata during capture. This preliminary organization enables rapid retrieval and sharing of specific moments without requiring complete reconstruction of the entire timelapse sequence, thus improving social sharing speed while maintaining immersion quality for the shared content.
Data Source
AI summary
A system captures via one or more sensors of a computing device, data of an environment observed by the one or more sensors at a first timeslot, and stores the data in a data store as a first portion of a timelapse memory experience. The system also captures, via the one or more sensors of a computing device, data of the environment observed by the one or more sensors at a second timeslot, and stores the data in a data store as a second portion of the timelapse memory experience. The system additionally associates the timelapse memory experience with a memory experience trigger, wherein the memory experience trigger can initiate a presentation of the timelapse memory experience.