• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Video Saliency Detection Using Bi-directional LSTM

Vol. 14, No. 6, June 30, 2020
10.3837/tiis.2020.06.007, Download Paper (Free):

Abstract

Significant detection of video can more rationally allocate computing resources and reduce the amount of computation to improve accuracy. Deep learning can extract the edge features of the image, providing technical support for video saliency. This paper proposes a new detection method. We combine the Convolutional Neural Network (CNN) and the Deep Bidirectional LSTM Network (DB-LSTM) to learn the spatio-temporal features by exploring the object motion information and object motion information to generate video. A continuous frame of significant images. We also analyzed the sample database and found that human attention and significant conversion are time-dependent, so we also considered the significance detection of video cross-frame. Finally, experiments show that our method is superior to other advanced methods.


Statistics

Show / Hide Statistics

Statistics (Cumulative Counts from December 1st, 2015)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article

[IEEE Style]
Y. Chi and J. Li, "Video Saliency Detection Using Bi-directional LSTM," KSII Transactions on Internet and Information Systems, vol. 14, no. 6, pp. 2444-2463, 2020. DOI: 10.3837/tiis.2020.06.007.

[ACM Style]
Yang Chi and Jinjiang Li. 2020. Video Saliency Detection Using Bi-directional LSTM. KSII Transactions on Internet and Information Systems, 14, 6, (2020), 2444-2463. DOI: 10.3837/tiis.2020.06.007.

[BibTeX Style]
@article{tiis:23587, title="Video Saliency Detection Using Bi-directional LSTM", author="Yang Chi and Jinjiang Li and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2020.06.007}, volume={14}, number={6}, year="2020", month={June}, pages={2444-2463}}