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المؤلفmaadeed, Somaya
المؤلفAlMaadeed, Noor
المؤلفelharrouss, omar
تاريخ الإتاحة2020-10-25T08:10:18Z
تاريخ النشر2020
اسم المنشورQatar University Annual Research Forum & Exhibition 2020
الاقتباسmaadeed S., AlMaadeed N., elharrouss o., "Face recognition and summarization for surveillance video sequences", Qatar University Annual Research Forum and Exhibition (QUARFE 2020), Doha, 2020, https://doi.org/10.29117/quarfe.2020.0235
معرّف المصادر الموحدhttps://doi.org/10.29117/quarfe.2020.0235
معرّف المصادر الموحدhttp://hdl.handle.net/10576/16649
الملخصFace 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
اللغةen
الناشرQatar University Press
الموضوعFace recognition
Deep learning
Action recognition.
العنوانFace recognition and summarization for surveillance video sequences
النوعPoster
dc.accessType Open Access


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