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http://hdl.handle.net/1942/25924
Title: | A Novel Hardware-Oriented Stereo Matching Algorithm and Its Architecture Design in FPGA | Authors: | LI, Yanzhe Huang, Kai CLAESEN, Luc |
Issue Date: | 2017 | Publisher: | Springer-Verlag | Source: | Hollstein, Thomas; Raik, Jaan; Kostin, Sergei; Tšertov, Anton; O'Connor, Ian; Reis, Ricardo (Ed.). VLSI-SoC: System-on-Chip in the Nanoscale Era – Design, Verification and Reliability, Springer Nature, p. 213-232 | Series/Report: | IFIP Advances in Information and Communication Technology | Series/Report no.: | 508 | Abstract: | Stereo matching is a crucial step to extract depth information from stereo images. However, it is still challenging to achieve good performance in both speed and accuracy for various stereo vision applications. In this contribution, a hardware-compatible stereo matching algorithm is proposed and its associated hardware implementation is also presented. The proposed algorithm can produce high-quality disparity maps with the combined use of the mini-census transform, segmentation-based adaptive support weight and effective refinement. Moreover, the proposed architecture is optimized as a fully pipelined and scalable hardware system. Implemented on an Altera Stratix-IV FPGA board, it can achieve 65 frames per second (fps) for 1024 × 768 stereo images and a 64 pixel disparity range. The proposed system is evaluated on the Middlebury benchmark and the average error rate is 6.56%. The experimental results indicate that the accuracy is competitive with some state-of-the-art software implementations. | Notes: | Li, YZ (reprint author), Zhejiang Univ, Inst VLSI Design, Hangzhou, Zhejiang, Peoples R China. liyz@vlsi.zju.edu.cn; huangk@vlsi.zju.edu.cn; luc.claesen@uhasselt.be | Keywords: | stereo matching; hardware implementation; system-on-chip; fpga; disparity calculation; computer vision. | Document URI: | http://hdl.handle.net/1942/25924 | ISBN: | 9783319671031 | DOI: | 10.1007/978-3-319-67104-8_11 | ISI #: | 000432573400011 | Rights: | (c) IFIP International Federation for information Processing 2017 | Category: | C1 | Type: | Proceedings Paper | Validations: | ecoom 2019 |
Appears in Collections: | Research publications |
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Claesen2018.pdf Restricted Access | Published version | 2.4 MB | Adobe PDF | View/Open Request a copy |
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