1. 中国科学院 机构 上海高等研究院,上海,201210
2. 中国科学院大学 机构,北京,101408
3. 上海科技大学 机构 信息科学与技术学院,上海,201210
纸质出版:2018
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陈明明, 祝永新, 田犁, 封松林, 汪辉. 基于FPGA的双目实时测距算法设计[J]. 微电子学与计算机, 2018, 35(10): 67-71.
CHEN Ming-ming, ZHU Yong-xin, TIAN Li, et al. Design of Binocular Real-Time Distance Measurement Algorithm Based on FPGA[J]. 2018, 35(10): 67-71.
为了克服软件层面实现双目测距算法实时性差的缺点
提出了一种基于FPGA的高速的双目测距算法的硬件架构
该架构使用并行流水线的结构来实现兴趣点的检测与描述
通过乒乓操作来实现描述向量的缓存与处理
同时通过WTA(Winner Takes All)电路和三角测量法来实现视差的搜索和距离的测量.实验结果表明:在25 MHz的时钟频率下
处理640×480的图像对只需12.5 ms
处理速度约为软件上的68倍
满足了高速场景下实时性的需求.同时
处理速度和资源消耗也优于一些相关硬件实现的文献.
In order to overcome the shortcomings of poor real-time performance of the binocular distance measurement algorithm on the software level
we present a high-speed hardware architecture of binocular distance measurement algorithm based on FPGA
the architecture uses a parallel pipeline structure to detect and describe interest points
and description vectors caching and processing is achieved by the ping-pong operation
disparity search and distance measurement are realized by WTA (Winner takes All) circuit and triangulation method simultaneously. The experimental results show that it only takes 12.5ms to deal with a pair of 640×480 images at the clock frequency of 25 MHz
and the processing speed is about 68 times of the software
it meets the real-time needs of some high-speed scenes. Simultaneously
the processing speed and resource consumption are also better than some related hardware implementations.
Bay H, Ess A, Tuytelaars T, et al. Speeded-up robust features (SURF) [J]. Computer Vision and Image Understanding, 2008, 110(3): 346-59. DOI: 346
徐彦泓, 朱云芳, 杜歆, 等.非参数化立体匹配算法的FPGA实现[J].浙江大学学报(工学版), 2009, 53(2): 250-254. DOI: 250
单洁, 唐垚, 姜晖.双目立体相机中实时匹配算法的FPGA实现[J].激光与红外, 2013, 43(12): 1406-1416. DOI: 1406
Lowe D G. Distinctive image features from scale-invariant keypoints [J]. International Journal of Computer Vision, 2004, 60(2): 91-110. DOI: 91
Fan X, Wu C, Cao W, et al. Implementation of high performance hardware architecture of OpenSURF algorithm on FPGA[C]//proceedings of the 2013 International Conference on Field-Programmable Technology (FPT). Kyoto, Japan, 2013.
丁帅帅, 柴志雷.基于HLS的SURF特征提取硬件加速单元设计与实现[J].微电子学与计算机, 2015, 33(9): 133-140. DOI: 133
Dalal N, Triggs B. Histograms of oriented gradients for human detection[C]//proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005. San Diego, CA, 2005.
赵勋杰, 李成金.双目立体实时测距系统的关键技术研究[J].激光与红外, 2006, 35(9): 874-881. DOI: 874
Wang C, Sun Y. A new method of depth measurement with binocular vision based on SURF[C]// proceedings of the International Workshop on Computer Science and Engineering, 2010.
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