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Multimedia image and video retrieval based on an improved HMM

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Abstract

In today's information age, information is gathered from text and more complex media, such as images, audio, and video. Among these data sources, the rapid growth of video information has led to it to gradually become the main source of information in people's lives. Video information is characterized by many kinds of information, complex forms, and a low degree of structure. Therefore, effectively classifying, managing and retrieving video information has become a difficult problem to solve. In this paper, an improved crow search algorithm is used to process video images, and the information entropy is used to extract the key frames, which reduces the computation burden of each frame feature calculation and feature contrast process, thus shortening the key frame detection time. Then, all the feature sets are extracted and used as input for an HMM according to the observed sequence \(O = O_{1} ,O_{2} ,O_{3} , \cdot \cdot \cdot ,O_{T}\) of the input image or video data and the initial model parameters \(\lambda = (\pi ,A,B)\). According to the training rules, the model parameters are repeatedly adjusted and modified, and the new model \(\overline{\lambda }\) is constructed step by step to realize the retrieval of multimedia images and videos. The experimental results show that the method has obvious advantages in terms of the retrieval time and retrieval effect and provides new ideas for multimedia image and video retrieval.

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Acknowledgements

This study was partially funded by The Institute of Tibetan Plateau Research, Chinese Academy of Sciences.

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Authors and Affiliations

  1. Key Laboratory of Continental Collision and Plateau Uplift, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100085, China

    Yanbing Liu & Sanjev Dhakal

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Yanbing Liu & Sanjev Dhakal

  3. Chengdu University of Technology, Chengdu, 610059, China

    Binyao Hao

Authors
  1. Yanbing Liu
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  2. Sanjev Dhakal
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  3. Binyao Hao
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Correspondence to Yanbing Liu.

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Liu, Y., Dhakal, S. & Hao, B. Multimedia image and video retrieval based on an improved HMM. Multimedia Systems 28, 2093–2103 (2022). https://doi.org/10.1007/s00530-020-00686-1

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  • DOI: https://doi.org/10.1007/s00530-020-00686-1

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