High Performance Stereo System for Dense 3-D Reconstruction

Michailidis, Georgios-Tsampikos; Pajarola, Renato; Andreadis, Ioannis

doi:10.1109/tcsvt.2013.2290575

Cited by 22 publications

(11 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In literature, various researchers have employed FPGA for image processing applications [20][21][22][23][24]. The authors of [25] presented an FPGA hardware architecture for real-time disparity map computation. In [26], authors developed a real-time stereo-view image-based rendering on FPGA.…”

Section: Related Workmentioning

confidence: 99%

Design of an FPGA Hardware Optimizing the Performance and Power Consumption of a Plenoptic Camera Depth Estimation Algorithm

Bhatti¹,

Greiner²

2021

Algorithms

View full text Add to dashboard Cite

Plenoptic camera based system captures the light-field that can be exploited to estimate the 3D depth of the scene. This process generally consists of a significant number of recurrent operations, and thus requires high computation power. General purpose processor based system, due to its sequential architecture, consequently results in the problem of large execution time. A desktop graphics processing unit (GPU) can be employed to resolve this problem. However, it is an expensive solution with respect to power consumption and therefore cannot be used in mobile applications with low energy requirements. In this paper, we propose a modified plenoptic depth estimation algorithm that works on a single frame recorded by the camera and respective FPGA based hardware design. For this purpose, the algorithm is modified for parallelization and pipelining. In combination with efficient memory access, the results show good performance and lower power consumption compared to other systems.

show abstract

Section: Related Workmentioning

confidence: 99%

Design of an FPGA Hardware Optimizing the Performance and Power Consumption of a Plenoptic Camera Depth Estimation Algorithm

Bhatti¹,

Greiner²

2021

Algorithms

View full text Add to dashboard Cite

show abstract

“…Due to these reasons, a number of additional intermediate frames need to be generated. There are numerous ways of generating intermediate frames, such as basic interpolation between input images, flow-field interpolation [61], image-based rendering [2,6], and structure approximation [1,5,15,17,31,34,38,45,58,60] to create depth mesh.…”

Section: Scene Depth Approximationmentioning

confidence: 99%

Kinetic depth images: flexible generation of depth perception

2016

View full text Add to dashboard Cite

In this paper we present a systematic approach to create smoothly varying images from a pair of photographs to facilitate enhanced awareness of the depth structure of a given scene. Since our system does not rely on sophisticated display technologies such as stereoscopy or auto-stereoscopy for depth awareness, it (a) is inexpensive and widely accessible, (b) does not suffer from vergence -accommodation fatigue, and (c) works entirely with monocular depth cues. Our approach enhances the depth awareness by optimizing across a number of features such as depth perception, optical flow, saliency, centrality, and disocclusion artifacts. We report the results of user studies that examine the relationship between depth perception, relative velocity, spatial perspective effects, and the positioning of the pivot point and use them when generating kinetic-depth images. We also present a novel depth re-mapping method guided by perceptual relationships based on the results of our user study. We validate our system by presenting a user study that compares the output quality of our proposed method against other existing alternatives on a wide range of images.

show abstract

“…W ITH the development of 3D technology [1]- [4], stereo image sources are increasing around the world, which allows people to see the stereo images on the screen. However, some stereo image sources suffer from various kinds of distortions which may cause visual discomforts like dizziness, nausea, and the declining of the body balance.…”

Section: Introductionmentioning

confidence: 99%