Abstract

We evaluated depth perception from motion parallax with capturing natural scene. First, we used two type control methods for the pickup device in capturing the natural scene. One control method was just horizontally repetition motion; another was horizontally repetition motion with heading to a fixation point. As a result, the latter method generated a clearer depth perception than that of the former method. Next, the position of the pickup device and the subject's head was changed for the latter method, when the test image sequences were evaluated. In this case, even when the relationship of the position between the pickup device and the subject's head was correct or opposite, the degree of depth perception was almost the same. These results suggest that the set of fixation point and the natural depth cue are important for depth perception from motion parallax with capturing the natural scene.

© 2015 IEEE

Motion-parallax smoothness of short-, medium-, and long-distance 3D image presentation using multi-view displays

Yasuhiro Takaki, Yohei Urano, and Hiroyuki Nishio
Opt. Express 20(24) 27180-27197 (2012)

Annular sector elemental image array generation method for tabletop integral imaging 3D display with smooth motion parallax

Yan Xing, Yun-Peng Xia, Shuang Li, Hui Ren, and Qiong-Hua Wang
Opt. Express 28(23) 34706-34716 (2020)

Super multi-view windshield display for long-distance image information presentation

Yasuhiro Takaki, Yohei Urano, Shinji Kashiwada, Hiroshi Ando, and Koji Nakamura
Opt. Express 19(2) 704-716 (2011)

Large viewing angle three-dimensional display with smooth motion parallax and accurate depth cues

Xunbo Yu, Xinzhu Sang, Xin Gao, Zhidong Chen, Duo Chen, Wei Duan, Binbin Yan, Chongxiu Yu, and Daxiong Xu
Opt. Express 23(20) 25950-25958 (2015)

Demonstration of a low-crosstalk super multi-view light field display with natural depth cues and smooth motion parallax

Peiren Wang, Xinzhu Sang, Xunbo Yu, Xin Gao, Binbin Yan, Boyang Liu, Li Liu, Chao Gao, Yang Le, Yuanhang Li, and Jingyan Du
Opt. Express 27(23) 34442-34453 (2019)