Reconfigurable hardware implementation of a phase-correlation stereoalgorithm

Darabiha, A.; MacLean, J.; Rose, Jonathan

doi:10.1007/s00138-006-0018-2

Cited by 41 publications

(29 citation statements)

References 26 publications

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“…Moreover phase-based techniques can be implemented on hardware as well. The algorithm implemented in (Darabiha et al 2006) is called Local Weighted Phase-Correlation (LWPC). Hardware implementation of the algorithm turns out to be more than 300 times faster than the software one.…”

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confidence: 99%

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Review of Stereo Vision Algorithms: From Software to Hardware

Nalpantidis

Sirakoulis

Γαστεράτος

2008

International Journal of Optomechatronics

347

159

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Stereo vision, resulting in the knowledge of deep information in a scene, is of great importance in the field of machine vision, robotics and image analysis. In this article, an explicit analysis of the existing stereo matching methods, up to date, is presented. The presented algorithms are discussed in terms of speed, accuracy, coverage, time consumption, and disparity range. Towards the direction of real-time operation, the development of stereo matching algorithms, suitable for efficient hardware implementation is highly desirable. Implementations of stereo matching algorithms in hardware for real-time applications are also discussed in details.

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mentioning

confidence: 99%

“…The speed for 640 Â 480 pixel images with 128 disparity levels is 30 fps. The hardware resources demanded are roughly the same as in (Darabiha et al 2006) due to the reuse of the available temporal information of the input video sequence.…”

mentioning

confidence: 99%

Review of Stereo Vision Algorithms: From Software to Hardware

Nalpantidis

Sirakoulis

Γαστεράτος

2008

International Journal of Optomechatronics

347

159

View full text Add to dashboard Cite

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“…There exist multiple approaches to optimize algorithms for embedded and real-time systems such as using low level languages (e.g. C, Assembler) using multi-processor boards for parallel computing or coding the algorithm in a field programmable gate-array (FPGA) [13,14].…”

Section: Designmentioning

confidence: 99%

A Matlab-Based Testbed for Integration, Evaluation and Comparison of Heterogeneous Stereo Vision Matching Algorithms

2016

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Stereo matching is a heavily researched area with a prolific published literature and a broad spectrum of heterogeneous algorithms available in diverse programming languages. This paper presents a Matlab-based testbed that aims to centralize and standardize this variety of both current and prospective stereo matching approaches. The proposed testbed aims to facilitate the application of stereo-based methods to real situations. It allows for configuring and executing algorithms, as well as comparing results, in a fast, easy and friendly setting. Algorithms can be combined so that a series of processes can be chained and executed consecutively, using the output of a process as input for the next; some additional filtering and image processing techniques have been included within the testbed for this purpose. A use case is included to illustrate how these processes are sequenced and its effect on the results for real applications. The testbed has been conceived as a collaborative and incremental open-source project, where its code is accessible and modifiable, with the objective of receiving contributions and releasing future versions to include new algorithms and features. It is currently available online for the research community.

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“…The phase-based computational model provided another alternative to correlation methods [40,41]. Diaz et al [42] developed a phase-based stereo vision design which generates about 20 stereo disparities using 1280 × 960 pixel images.…”

Section: Related Studiesmentioning

confidence: 99%

Real-time stereo vision system using adaptive weight cost aggregation approach

Ding

Liu

Zhou

et al. 2011

J Image Video Proc.

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Many vision applications require high-accuracy dense disparity maps in real time. Due to the complexity of the matching process, most real-time stereo applications rely on local algorithms in the disparity computation. These local algorithms generally suffer from matching ambiguities as it is difficult to find appropriate support for each pixel. Recent research shows that algorithms using adaptive cost aggregation approach greatly improve the quality of disparity map. Unfortunately, although these improvements are excellent, they are obtained at the expense of high computational. This article presents a hardware implementation for speeding up these methods. With hardware friendly approximation, we demonstrate the feasibility of implementing this expensive computational task on hardware to achieve real-time performance. The entire stereo vision system, includes rectification, stereo matching, and disparity refinement, is realized using a single field programmable gate array. The highly parallelized pipeline structure makes system be capable to achieve 51 frames per second for 640 × 480 stereo images. Finally, the success of accuracy improvement is demonstrated on the Middlebury dataset, as well as tests on real scene.

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Reconfigurable hardware implementation of a phase-correlation stereoalgorithm

Cited by 41 publications

References 26 publications

Review of Stereo Vision Algorithms: From Software to Hardware

Review of Stereo Vision Algorithms: From Software to Hardware

A Matlab-Based Testbed for Integration, Evaluation and Comparison of Heterogeneous Stereo Vision Matching Algorithms

Real-time stereo vision system using adaptive weight cost aggregation approach

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