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GPU-Accelerated Single Image Depth Estimation with Color-Filtered Aperture
  • KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

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

Vol. 8, No. 3, March 30, 2014
10.3837/tiis.2014.03.020, Download Paper (Free):

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.


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Cite this article

[IEEE Style]
Y. Hsu, C. Chen and S. Tseng, "GPU-Accelerated Single Image Depth Estimation with Color-Filtered Aperture," KSII Transactions on Internet and Information Systems, vol. 8, no. 3, pp. 1058-1070, 2014. DOI: 10.3837/tiis.2014.03.020.

[ACM Style]
Yueh-Teng Hsu, Chun-Chieh Chen, and Shu-Ming Tseng. 2014. GPU-Accelerated Single Image Depth Estimation with Color-Filtered Aperture. KSII Transactions on Internet and Information Systems, 8, 3, (2014), 1058-1070. DOI: 10.3837/tiis.2014.03.020.