Earticle

초록

영어

Compared with the two-dimensional media, the image depth of three-dimensional media can offer more intuitive and real scenes to the audience for feeling. But with the development of 3D display machines, there is a serious contradiction between the rapid of the 3D display machines and the lack of resources for the machines. To solve the problem, proposed an efficient image depth extraction method which utilizes the support vector machine (SVM). The label is established from the true depth of different videos, and the vector feature, haze is utilized as the feature vector. The training set is divided into a number of small training sets, reducing the sample size of the training sets, in order to improve training speed. The experimental results show that the algorithm is effective.

목차

Abstract
 1. Introduction
 2. Depth of Image Extraction Method
 3. The Depth Extraction Methods based on Support Vector Machine
  3.1. Support Vector Machine
  3.2 Depth extraction based on support vector machine
 4. Image Depth Extraction Method
  4.1. Classification and acquisition of Labeling
  4.2. Extract Feature Vector
  4.3. Experimental Results
 5. Conclusions
 References

키워드

저자

• Zhipeng Fan [ School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China ]
• Mingjun Li [ School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China ]
• Ying Lu [ School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605