The DOI matches its Crossref record; 24 of the 27 references it cites were found in a registry or an index.
Event Retrieval in Large Video Collections with Circulant Temporal Encoding
Open accessAbstract
This paper presents an approach for large-scale event retrieval. Given a video clip of a specific event, eg, the wedding of Prince William and Kate Middleton, the goal is to retrieve other videos representing the same event from a dataset of over 100k videos. Our approach encodes the frame descriptors of a video to jointly represent their appearance and temporal order. It exploits the properties of circulant matrices to compare the videos in the frequency domain. This offers a significant gain in complexity and accurately localizes the matching parts of videos. Furthermore, we extend product quantization to complex vectors in order to compress our descriptors, and to compare them in the compressed domain. Our method outperforms the state of the art both in search quality and query time on two large-scale video benchmarks for copy detection, Trecvid and CCWeb. Finally, we introduce a challenging dataset for event retrieval, EVVE, and report the performance on this dataset.
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In the citing paper
“However, there does not seem to be strong consensus among researchers about which videos are considered near-duplicate videos and none of the existing definitions addresses the retrieval of same incident videos ; in this paper, we attempt to address these issues and provide solid definitions for all types of associations between videos related to the FIVR problem.”
From FIVR: Fine-Grained Incident Video Retrieval (2019) · cites this paper as [35]
In the citing paper
“We also implemented this pipeline on VCDB but observed slightly worse results than the adopted baseline.”
From VCDB: A Large-Scale Database for Partial Copy Detection in Videos (2014) · cites this paper as [16]
In the citing paper
“This is probably because the approach was designed for similar video event retrieval, which emphasizes more on similar semantics, not necessarily the same visual patterns, and therefore did not enforce strong geometric consistency of the matched local feature points.”
From VCDB: A Large-Scale Database for Partial Copy Detection in Videos (2014) · cites this paper as [16]
In the citing paper
“However, there does not seem to be strong consensus among researchers about which videos are considered near-duplicate videos and none of the existing definitions addresses the retrieval of same incident videos ; in this paper, we attempt to address these issues and provide solid definitions for all types of associations between videos related to the FIVR problem.”
From FIVR: Fine-Grained Incident Video Retrieval (2019) · cites this paper as [35]
In the citing paper
“In EVVE, the definition of the related videos is much more fuzzy, and additionally, the dataset contains annotations only for videos from the same event, and not for its near-duplicates.”
From FIVR: Fine-Grained Incident Video Retrieval (2019) · cites this paper as [35]
Citations
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3 of the 27 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- nowak, 2006, Sampling strategies for bag-offeatures image classification, ECCV
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Cordelia Schmid { Curriculum Vitae
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Video Classification Using Smooth Approximation of Hard-assignment Encoding
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Video Content Plagiarism Detection Using Region-Based Feature Learning
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Metadata
- Authors
- Revaud, J., Douze, M., Schmid, C., & Jegou, H.
- Affiliations
- Institut national de recherche en sciences et technologies du numérique (FR)
- Venue
- 2013 IEEE Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2013-06
- Pages
- 2459-2466
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2165502232
- Cited by
- 133
- References
- 27
- Citations by year
- 2026: 4 · 2025: 2 · 2024: 5 · 2023: 12 · 2022: 9 · 2021: 7 · 2020: 3 · 2019: 13 · 2018: 5 · 2017: 15 · 2016: 18 · 2015: 21 · 2014: 15 · 2013: 4
- FWCI
- 12.34
- Type
- conference paper
- Language
- en
- Open access
- green
- inria.hal.science
- Licence
- other-oa
- Locations
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (publishedVersion)
- HAL (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Analysis and Summarization
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Keywords
- event retrieval, circulant matrices, product quantization, video copy detection, TRECVID
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