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    Face recognition and summarization for surveillance video sequences

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    Face recognition and summarization for surveillance video sequences.pdf (491.6Kb)
    Date
    2020
    Author
    maadeed, Somaya
    AlMaadeed, Noor
    elharrouss, omar
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    Abstract
    Face recognition and video summarization represent chal- lenging tasks for several computer vision applications including video surveil- lance, criminal investigations, and sports applications'. For long videos, it is difficult to search within a video for a specific action and/or person. Usually, human action recognition approaches presented in the literature deal with videos that contain only a single person, and they are able to recognize his action. This paper proposes an effective approach to multiple human action detection, recognition, and summarization. The multiple action detection ex- tracts human bodies' silhouette then generates a specific sequence for each one of them using motion detection and tracking method. Each of the extracted sequences is then divided into shots that represent homogeneous actions in the sequence using the similarity between each pair frames. Using the histogram of the oriented gradient (HOG) of the Temporal Difference Map (TDMap) of the frames of each shot, we recognize the action by performing a comparison be- tween the generated HOG and the existed HOGs in the training phase which represents all the HOGs of many actions using a set of videos for training
    URI
    https://doi.org/10.29117/quarfe.2020.0235
    DOI/handle
    http://hdl.handle.net/10576/16649
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    • Theme 3: Information and Communication Technologies [‎19‎ items ]

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