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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 1
317-320

Research on video description based on deep bidirectional model and feature fusion

Ning Peiyang
Shi Jinglun
Zhang Rongfeng
Qiu Wei
School of Electronic & Information Engineering, South China University of Technology, Guangzhou 510640, China
DOI: 10.19734/j.issn.1001-3695.2018.03.0488

Abstract

Automatically generating a natural language description of a video is a challenging work for computer vision. The method based on deep bidirectional long-short term memory(DBLSTM) and CNN feature, has the ability to learn global spatiotemporal correlation information of videos. Focusing on the low accuracy and high computational complexity of video to text, this paper proposed a new method, which based on the deep bidirectional minimal gated unit(BMGU) in order to improve the computational efficiency while maintaining the advantages in structure of the deep BLSTM model. In the same time, by merging the CNN feature of the original frames and the CNN feature of the frames with Haar feature increased the diversity of training features and improved the effect of the video to text. By using the datasets of M-VAD and MPII-MD, comparing to the original S2VT model, the proposed method increased the scores from 6.7 to 8.0 and from 7.1 to 8.3 in METEOR. The results show that the proposed method can effectively improve the accuracy and the description of the videos of the original S2VT model.

Foundation Support

国家自然科学基金资助项目(61671213)
广州市人体数据科学重点实验室基金资助项目(201605030011)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.03.0488
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 1
Section: Technology of Graphic & Image
Pages: 317-320
Serial Number: 1001-3695(2020)01-068-0317-04

Publish History

[2020-01-05] Printed Article

Cite This Article

宁培阳, 史景伦, 张荣锋, 等. 基于深度双向模型和特征融合的视频转文字研究 [J]. 计算机应用研究, 2020, 37 (1): 317-320. (Ning Peiyang, Shi Jinglun, Zhang Rongfeng, et al. Research on video description based on deep bidirectional model and feature fusion [J]. Application Research of Computers, 2020, 37 (1): 317-320. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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