MemoryDiorama: Generating Dynamic 3D Diorama from Everyday Photos for Memory Recall

TL;DR

MemoryDiorama creates dynamic 3D dioramas from personal photos using AI to enhance autobiographical memory recall through richer, animated contextual cues.

Contribution

It introduces a novel system that transforms personal photos into animated 3D dioramas with AI-generated contextual details to improve memory recall.

Findings

MemoryDiorama elicited more internal and in-cue details during recall.

It increased perceptual details and visual vividness ratings.

Participants experienced richer recollective experiences.

Abstract

We present MemoryDiorama, a prototype system that introduces augmented memory cues, a concept that extends captured personal media with AI-generated contextual information to enhance autobiographical memory recall. MemoryDiorama transforms everyday photos into dynamic 3D dioramas in mixed reality by integrating LLM-based scene analysis with 3D object generation, animation, and spatial composition. The system extracts geographic information, object attributes, lighting conditions, and atmospheric elements from the photos. It then animates these elements with generative components such as object animations, human motion, geographical effects, and particle effects to provide richer cues for memory recall. We evaluated MemoryDiorama in a within-subject user study with 18 participants, comparing three conditions: Photo-Only, Static Diorama, and MemoryDiorama. Compared with both Photo-Only and Static Diorama, MemoryDiorama elicited more internal and in-cue details during recall. It also increased perceptual details and visual vividness ratings, suggesting richer recollective experience.