Abstract
As the coal mine environment is similar to night-time, there is less discernible information, which makes the coal mine video images collected by the camera have a high level of redundancy, less available information, obvious light spots, and noise interference, which are not conducive to extracting useful information from the video. In view of the above problems, a keyframes extraction algorithm for coal mine video images based on a secondary filter with adaptive Top-K is proposed. The algorithm calculates the eigenvalues of the feature points using the principal component analysis method, then filters the eigenvalues by the threshold of adaptive Top-K to extract the effective keyframes of the coal mine image. The experimental results show that the algorithm can extract the keyframes more accurately using the adaptive threshold method.
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Fu, Y., Xu, C., Wang, M. (2020). Secondary Filter Keyframes Extraction Algorithm Based on Adaptive Top-K. In: Lu, H., Yujie, L. (eds) 2nd EAI International Conference on Robotic Sensor Networks. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-17763-8_16
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DOI: https://doi.org/10.1007/978-3-030-17763-8_16
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