Publication details

Visual Descriptors in Methods for Video Hyperlinking

Authors

GALUŠČÁKOVÁ Petra BATKO Michal ČECH Jan MATAS Jiří NOVÁK David PECINA Pavel

Year of publication 2017
Type Article in Proceedings
Conference Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval
MU Faculty or unit

Faculty of Informatics

Citation
Doi http://dx.doi.org/10.1145/3078971.3079026
Field Informatics
Keywords Video retrieval; Hyperlinking; Information retrieval; Image processing
Description In this paper, we survey different state-of-the-art visual processing methods and utilize them in hyperlinking. Visual information, calculated using Features Signatures, SIMILE descriptors and convolutional neural networks (CNN), is utilized as similarity between video frames and used to find similar faces, objects and setting. Visual concepts in frames are also automatically recognized and textual output of the recognition is combined with search based on subtitles and transcripts. All presented experiments were performed in the Search and Hyperlinking 2014 MediaEval task and Video Hyperlinking 2015 TRECVid task.
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