Face-based People Searching in Videos

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Authors

SEDMIDUBSKÝ Jan BATKO Michal ZEZULA Pavel

Year of publication 2013
Type Article in Proceedings
Conference 35th European Conference on Information Retrieval (ECIR 2013), LNCS 7814
MU Faculty or unit

Faculty of Informatics

Citation
Doi http://dx.doi.org/10.1007/978-3-642-36973-5_101
Field Informatics
Keywords face recognition; video retrieval; similarity search; MPEG-7
Description We propose a system for retrieving people according to their faces in unannotated video streams. The system processes input videos to extract key-frames on which faces are detected. The detected faces are automatically grouped together to create clusters containing snapshots of the same person. The system also facilitates annotation and manual manipulations with created clusters. On the processed videos the system offers to search for persons in three distinct operations applicable to various scenarios. The system is presented online by indexing five high-quality video streams with the total length of nearly five hours.
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