Triple-SGM: Stereo Processing using Semi-Global Matching with Cost Fusion

Kallwies, Jan; Engler, Torsten; Forkel, Bianca; Wuensche, Hans-Joachim

doi:10.1109/wacv45572.2020.9093372

Cited by 10 publications

(10 citation statements)

References 16 publications

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“…The semi-global stereo matching algorithm designed in this paper mainly includes the following steps: Census transform, Hamming distance calculation, cost aggregation, and disparity calculation [7] .…”

Section: Semi-global Stereo Matching Algorithmmentioning

confidence: 99%

Design of binocular vision system based on Zynq

Wang,

Gong,

Zhang

et al. 2023

Third International Conference on Signal Image Processing and Communication (ICSIPC 2023)

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Binocular vision is an important branch of computer vision that processes images captured from two different cameras with different perspectives to obtain depth information of a scene. However, the stereo matching algorithm is complex and traditional platforms often struggle to meet real-time and accuracy requirements simultaneously. In this article, we implement a binocular vision system based on the idea of software-hardware co-design on the Zynq platform. According to the characteristics of the Zynq platform, the system's software and hardware functions are divided. The processing system (PS) is mainly responsible for flow control and binocular correction, while the programmable logic (PL) is responsible for parallel acceleration of the stereo matching algorithm. In the image acquisition part, we configure the format and output image timing using a designed camera acquisition module. In the stereo matching part, we design a semi-global stereo matching algorithm using Verilog language. Finally, we build a binocular vision system on the Zynq platform for testing. The experimental results show that the frame rate can reach 30fps when the input image resolution is 640×480, which satisfies the requirements of real-time and accuracy of the output disparity map.

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Section: Semi-global Stereo Matching Algorithmmentioning

confidence: 99%

Design of binocular vision system based on Zynq

Wang,

Gong,

Zhang

et al. 2023

Third International Conference on Signal Image Processing and Communication (ICSIPC 2023)

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“…To understand 3D Projection Systems based on Stereo Matching, we take [14] as a guide for studying Global Matching-based 3D Projection System, such as [15,16] which propose Dynamic Programming (DP), and Semi-global Matching-based 3D Projection System, such as [17,18] which is more suitable for hardware implementation.…”

Section: Related Workmentioning

confidence: 99%

Weighted Least Square Filter for Improving the Quality of Depth Map on FPGA

Mao

Wei

Amano

et al. 2022

IJNC

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This paper proposes a post-filtering system for improving the quality of depth maps for 3D projection on FPGA. We propose to implement the Weighted Least Square (WLS) filter on Field-programmable Gate Array (FPGA), which can predict the disparities, which cannot be measured, by using the values of the neighboring pixels. In our design, we optimized the architecture of WLS filter at the algorithm level. For hardware acceleration, we use the High-Level Synthesis (HLS) description to accelerate the algorithm. To break through the bottleneck brought by the limited memory resources on FPGA, we used UltraScale Architecture Memory Resources (URAM) on board and reduced memory consumption of Block RAMs (BRAM) from 140% to 80%. Through our approach, we can improve the quality of the depth map on the FPGA named M-KUBOS. And, the WLS filter can smooth the depth map with 130 MHz operational frequency on M-KUBOS at the speed of 10 frames per second (FPS), which achieves a 76.43% performance acceleration compared to the software execution on the ARM Cortex A9 at 1.2 GHz clock.

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“…In [26], the fusion was applied after computing the Sum of Squared Distances (SSD) of images. More recently, authors in [17,18] extended the standard two-view stereo to a three-view setup by adding a camera on top of the left one. This L-shape configuration creates a vertical and a horizontal baseline.…”

Section: Related Workmentioning

confidence: 99%

“…To the best of our knowledge, the proposed model is the first that processes the multi-baseline trinocular setting in an end-to-end deep learning-based manner. The previous multi-baseline stereo works [16][17][18] rely on traditional stereo approaches.…”

Section: Introductionmentioning

confidence: 99%

TriStereoNet: A Trinocular Framework for Multi-baseline Disparity Estimation

Shamsafar¹,

Zell²

2021

Preprint

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Stereo vision is an effective technique for depth estimation with broad applicability in autonomous urban and highway driving. While various deep learning-based approaches have been developed for stereo, the input data from a binocular setup with a fixed baseline are limited. Addressing such a problem, we present an end-to-end network for processing the data from a trinocular setup, which is a combination of a narrow and a wide stereo pair. In this design, two pairs of binocular data with a common reference image are treated with shared weights of the network and a mid-level fusion. We also propose a Guided Addition method for merging the 4D data of the two baselines. Additionally, an iterative sequential selfsupervised and supervised learning on real and synthetic datasets is presented, making the training of the trinocular system practical with no need to ground-truth data of the real dataset. Experimental results demonstrate that the trinocular disparity network surpasses the scenario where individual pairs are fed into a similar architecture. Code and dataset: https://github.com/cogsystuebingen/tristereonet.

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Triple-SGM: Stereo Processing using Semi-Global Matching with Cost Fusion

Cited by 10 publications

References 16 publications

Design of binocular vision system based on Zynq

Design of binocular vision system based on Zynq

Weighted Least Square Filter for Improving the Quality of Depth Map on FPGA

TriStereoNet: A Trinocular Framework for Multi-baseline Disparity Estimation

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