Abstract
AbstractThe past decades have seen an exponential growth in the amount of data which is produced by individuals. Smartphones which capture images, videos and sensor data have become commonplace, and wearables for fitness and health are growing in popularity. Lifelog retrieval systems aim to aid users in finding and exploring their personal history. We present two systems for lifelog retrieval: vitrivr and vitrivr-VR, which share a common retrieval model and backend for multi-modal multimedia retrieval. They differ in the user interface component, where vitrivr relies on a traditional desktop-based user interface and vitrivr-VR has a Virtual Reality user interface. Their effectiveness is evaluated at the Lifelog Search Challenge 2021, which offers an opportunity for interactive retrieval systems to compete with a focus on textual descriptions of past events. Our results show that the conventional user interface outperformed the VR user interface. However, the format of the evaluation campaign does not provide enough data for a thorough assessment and thus to make robust statements about the difference between the systems. Thus, we conclude by making suggestions for future interactive evaluation campaigns which would enable further insights.
Funder
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
University of Basel
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Reference46 articles.
1. Ang W-H, Yen A-Z, Chu T-T, Huang H-H, Chen H-H (2021) LifeConcept: an interactive approach for multimodal lifelog retrieval through concept recommendation. In: 4th annual on lifelog search challenge. Association for Computing Machinery, New York, pp 47–51. https://doi.org/10.1145/3463948.3469070
2. Barnes C, Goldman DB, Shechtman E, Finkelstein A. (2010) Video tapestries with continuous temporal zoom. ACM Trans Graph 29(4):89–1899. https://doi.org/10.1145/1778765.1778826
3. Cer D, Yang Y, Kong S-Y, Hua N, Limtiaco N, John RS, Constant N, Guajardo-Cespedes M, Yuan S, Tar C, Sung Y-H, Strope B, Kurzweil R (2018) Universal sentence encoder. arXiv:1803.11175
4. Gasser R, Rossetto L, Heller S, Schuldt H (2020) Cottontail DB: an open source database system for multimedia retrieval and analysis. In: Chen CW, Cucchiara R, Hua X-S, Qi G-J, Ricci E, Zhang Z, Zimmermann R (eds) International conference on multimedia (MM). Association for Computing Machinery, New York, pp 4465–4468. https://doi.org/10.1145/3394171.3414538
5. Gasser R, Rossetto L, Schuldt H (2019) Multimodal multimedia retrieval with vitrivr. In: International conference on multimedia retrieval (ICMR). Association for Computing Machinery, New York, pp 391–394. https://doi.org/10.1145/3323873.3326921
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. A Comparison of Video Browsing Performance between Desktop and Virtual Reality Interfaces;Proceedings of the 2023 ACM International Conference on Multimedia Retrieval;2023-06-12