Mnemonic Tracing: Using Eye Gaze to Search for Visual Memories

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Authors: Wazeer Deen Zulfikar, Yasith Samaradivakara, Paul Pu Liang, Pattie Maes
Cited by: 1
References: 32

Abstract

While modern image retrieval systems rely on natural language, some users struggle or are unable to verbalize specific visual memories. Drawing on gaze reinstatement research, we introduce mnemonic tracing: a non-verbal interaction where users intentionally externalize mental images by tracing them onto a blank space using eye gaze. We conducted a pilot study (N = 11) to evaluate retrieval of 30 images of people, objects, and locations using eye-tracking glasses. Without training data or prior user training, our system achieved Top-1 accuracy of 30.5% (compared to 3.3% chance level) and a Top-3 accuracy of 51.2%. We show performance is influenced by individual imagery vividness and task engagement, suggesting success is driven by active mental reconstruction. Highlighting its practical potential, participants reported moderately high perceived usefulness (M = 3.58/5, SD = 0.82) on the Technology Acceptance Model survey. The method offers a private, hands-free, and inclusive alternative for scenarios where a text- or voice-based search is inaccessible.

Fields of Study & Subjects

Gaze Tracking and Assistive Technology Visual Attention and Saliency Detection Hand Gesture Recognition Systems

Publication details

Journal / source
Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–9
Publication date
13 April 2026