Pocket Time-Lapse

Eric Ming Chen, Žiga Kovačič, Madhav Aggarwal, Abe Davis

Abstract: This paper explores how to record, explore, and visualize long-term changes in an environment—at the scale of days, months, and even years—based on data that a single user can conveniently capture using the mobile phone they already carry. Our strategy involves making the data capture process as quick and convenient as possible so that it is easy to integrate into daily routines. This strategy yields large unstructured panoramic image datasets, which we process using novel registration and scene reconstruction approaches. Our central contribution lies in demonstrating pocket time-lapse as a novel application, made possible through several key technical contributions. These include a novel method for quickly and robustly registering thousands of unstructured panoramic images, a novel reconstruction technique for rendering time-lapse and performing state-of-the-art intrinsic image decomposition, and several large hand-captured datasets that span multiple years of data collection, totaling over 6k separate capture sessions and 50k images.