A retrieval algorithm for specific face images in airport surveillance multimedia videos on cloud computing platform


During retrieval process for specific face images in the airport surveillance multimedia video on cloud computing platform, because pattern of faces are complicated and vulnerable to interference, when the traditional algorithm is used for face retrieval, the accuracy and efficiency are reduced and robustness is low. A new retrieval algorithm for specific face images is proposed, and this method is deployed to the cloud computing platform. Harr face cascade classifier is used to detect face images in airport surveillance multimedia video, in order to find out the missing face in airport surveillance multimedia video, the block matching method is introduced for face tracking, and the missing face in the video is obtained. PCA method is utilized to extract specific facial features, and discriminant analysis method is used to compare the extracted feature information with the specific face, so as to realize the specific face image retrieval. Experimental results show that the proposed algorithm has a high retrieval efficiency and precision.

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Correspondence to Hwa-Young Jeong.

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Zhang, N., Jeong, H. A retrieval algorithm for specific face images in airport surveillance multimedia videos on cloud computing platform. Multimed Tools Appl 76, 17129–17143 (2017). https://doi.org/10.1007/s11042-016-3640-7

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  • Airport security
  • Multimedia video
  • Specific face image
  • Retrieval
  • Cloud computing platform