6533b834fe1ef96bd129ce1b
RESEARCH PRODUCT
Keyword Based Keyframe Extraction in Online Video Collections
Giuseppe MazzolaEdoardo ArdizzoneMarco La Casciasubject
Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniInformation retrievalbusiness.industryComputer sciencemedia_common.quotation_subjectShot (filmmaking)InformationSystems_INFORMATIONSTORAGEANDRETRIEVALFrame (networking)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionDomain (software engineering)Factor (programming language)Metric (mathematics)Quality (business)SegmentationArtificial intelligencebusinesscomputerSentencemedia_commoncomputer.programming_languageVideo Summarization Keyframe Extraction Automatic Speech Recognition YouTube Multimedia Collectionsdescription
Keyframe extraction methods aim to find in a video sequence the most significant frames, according to specific criteria. In this paper we propose a new method to search, in a video database, for frames that are related to a given keyword, and to extract the best ones, according to a proposed quality factor. We first exploit a speech to text algorithm to extract automatic captions from all the video in a specific domain database. Then we select only those sequences (clips), whose captions include a given keyword, thus discarding a lot of information that is useless for our purposes. Each retrieved clip is then divided into shots, using a video segmentation method, that is based on the SURF descriptors and keypoints. The sentence of the caption is projected onto the segmented clip, and we select the shot that includes the input keyword. The selected shot is further inspected to find good quality and stable parts, and the frame which maximizes a quality metric is selected as the best and the most significant frame. We compare the proposed algorithm with another keyframe extraction method based on local features, in terms of Significance and Quality.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2015-01-01 |