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Review of stereo vision algorithms and their suitability for resource-limited systems

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Abstract

A significant amount of research in the field of stereo vision has been published in the past decade. Considerable progress has been made in improving accuracy of results as well as achieving real-time performance in obtaining those results. This work provides a comprehensive review of stereo vision algorithms with specific emphasis on real-time performance to identify those suitable for resource-limited systems. An attempt has been made to compile and present accuracy and runtime performance data for all stereo vision algorithms developed in the past decade. Algorithms are grouped into three categories: (1) those that have published results of real-time or near real-time performance on standard processors, (2) those that have real-time performance on specialized hardware (i.e. GPU, FPGA, DSP, ASIC), and (3) those that have not been shown to obtain near real-time performance. This review is intended to aid those seeking algorithms suitable for real-time implementation on resource-limited systems, and to encourage further research and development of the same by providing a snapshot of the status quo.

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Notes

  1. For all custom algorithm labellings and corresponding citations see Table 1.

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    Beau Tippetts, Dah Jye Lee, Kirt Lillywhite & James Archibald

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Tippetts, B., Lee, D.J., Lillywhite, K. et al. Review of stereo vision algorithms and their suitability for resource-limited systems. J Real-Time Image Proc 11, 5–25 (2016). https://doi.org/10.1007/s11554-012-0313-2

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