[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.3837/tiis.2014.03.020

GPU-Accelerated Single Image Depth Estimation with Color-Filtered Aperture

Hsu, Yueh-Teng (A-MTK Corp.)
Chen, Chun-Chieh (Department of Electronic Engineering, National Taipei University of Technology)
Tseng, Shu-Ming (Department of Electronic Engineering, National Taipei University of Technology)

Publication Information

KSII Transactions on Internet and Information Systems (TIIS) / v.8, no.3, 2014 , pp. 1058-1070 More about this Journal

Abstract

There are two major ways to implement depth estimation, multiple image depth estimation and single image depth estimation, respectively. The former has a high hardware cost because it uses multiple cameras but it has a simple software algorithm. Conversely, the latter has a low hardware cost but the software algorithm is complex. One of the recent trends in this field is to make a system compact, or even portable, and to simplify the optical elements to be attached to the conventional camera. In this paper, we present an implementation of depth estimation with a single image using a graphics processing unit (GPU) in a desktop PC, and achieve real-time application via our evolutional algorithm and parallel processing technique, employing a compute shader. The methods greatly accelerate the compute-intensive implementation of depth estimation with a single view image from 0.003 frames per second (fps) (implemented in MATLAB) to 53 fps, which is almost twice the real-time standard of 30 fps. In the previous literature, to the best of our knowledge, no paper discusses the optimization of depth estimation using a single image, and the frame rate of our final result is better than that of previous studies using multiple images, whose frame rate is about 20fps.

Keywords

Real time; graphics processing unit; parallel processing technique; compute shade;

Citations & Related Records

Times Cited By KSCI : 2 (Citation Analysis)

Reference
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