实时检测线段，仅扫描一次图像，内存占用极低。
SweepLSD: A One-Pass, O(width)-Memory Line Segment Detector with an Integer-Only Streaming Core and a Real-Time FPGA Realization
- 单次扫描图像，逐行处理，中间内存仅与图像宽度相关。
- 1080p视频实时处理，4K照片每帧仅需11毫秒，速度领先。
- 适合嵌入式设备或实时系统，内存占用远低于传统方法。
我们提出SweepLSD，一种线段检测器，仅读取图像一次，并在每个线段最后一个像素通过扫描线后的几行内输出该线段。所有阶段（包括连通域标记和最终线段检测）均以行流形式处理图像：中间内存为O(width)，而非O(pixels)，且每个像素核心仅使用整数运算。本文首次完整描述该算法，其设计源自作者2014年硕士论文但从未发表，同时提供开源C++17实现及FPGA实现——在硬件配置下与软件保持位级精确。该实现可在2009年旧款芯片上实时处理1080p30视频，无需帧缓冲或外部内存。在结构丰富的公共4K照片下采至全高清时，单个CPU线程检测耗时约11毫秒，比原始的ELSED、EDLines和LSD实现分别快4.6倍、5.2倍和25倍，具有最紧的帧时间分布和最佳的线段方向精度；天然具备曲线拒绝能力，但在合成真值上的F-score略逊于ELSED。在York Urban和NYU-VP数据集上，基于曼哈顿框架的消失点分析采用选择/评估分离的最佳估计器协议，SweepLSD在NYU-VP上领先约0.3度，在York Urban上落后0.1度，且在两个数据集上均为四者中端到端最快。单帧相机姿态应用在合成场景（带精确真值）、EuRoC和TUM-VI数据集上表现与基线相当，但内存消耗仅为几分之一，并在4K航向锁定任务中达到0.06度的中位姿态误差，单帧处理时间中位为32毫秒。
原文摘要 · Abstract (English)
We present SweepLSD, a line segment detector that reads the image exactly once and emits each segment within a few rows of its last pixel passing the scan line. Every stage, including connected-component labeling and the final line test, processes the image as a row stream: intermediate memory is O(width) rather than O(pixels), and the per-pixel core is integer-only. We give the first complete description of the algorithm, designed in the author's 2014 master's thesis but never published, together with an open-source C++17 implementation and an FPGA realization -- held bit-exact against the software in its hardware configuration -- detecting segments in live 1080p30 video on 2009-era silicon without frame buffer or external memory. On structure-rich public 4K photographs downscaled to Full-HD, one CPU thread detects segments in ~11 ms -- 4.6x/5.2x/25x faster than the original authors' implementations of ELSED, EDLines, and LSD -- with the tightest frame-time distribution and the best per-segment direction accuracy of the four detectors, and curve rejection by design, while trailing ELSED in F-score on synthetic ground truth. A Manhattan-frame vanishing-point study on York Urban and NYU-VP scores every detector under a selection/evaluation-separated best-estimator-per-detector protocol, under which SweepLSD leads on NYU-VP by ~0.3 degrees and trails by 0.1 degrees on York Urban, with the fastest end-to-end pipeline of the four detectors on both. A single-frame camera-attitude application, evaluated on synthetic scenes with exact ground truth and on EuRoC and TUM-VI, matches the baselines' accuracy at a fraction of their memory, and drives a 4K horizon lock to 0.06 degrees median attitude error at 32 ms median per frame.
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