Event Retrieval in Large Video Collections with Circulant Temporal Encoding
- 1 June 2013
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 2459-2466
- https://doi.org/10.1109/cvpr.2013.318
Abstract
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.Keywords
This publication has 16 references indexed in Scilit:
- Three things everyone should know to improve object retrievalPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2012
- Multiple feature hashing for real-time large scale near-duplicate video retrievalPublished by Association for Computing Machinery (ACM) ,2011
- Tiny Videos: A Large Data Set for Nonparametric Video Retrieval and Frame ClassificationIEEE Transactions on Pattern Analysis and Machine Intelligence, 2010
- Product Quantization for Nearest Neighbor SearchIEEE Transactions on Pattern Analysis and Machine Intelligence, 2010
- Practical elimination of near-duplicates from web video searchPublished by Association for Computing Machinery (ACM) ,2007
- Video copy detectionPublished by Association for Computing Machinery (ACM) ,2007
- Object retrieval with large vocabularies and fast spatial matchingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2007
- Evaluation campaigns and TRECVidPublished by Association for Computing Machinery (ACM) ,2006
- Distinctive Image Features from Scale-Invariant KeypointsInternational Journal of Computer Vision, 2004
- A survey of image registration techniquesACM Computing Surveys, 1992