OpenCV激光投影虚拟键盘 基于激光投影技术的虚拟键盘设计基于OpenCV，结合硬件识别，检测手指位置，然后映射到键盘，以实现相应的KeyPress。 如何工作？ 如何工作？ 在红外激光的底部从一个红外范围内的覆盖空间的表面发射出红外线，当然这个平面可以覆盖整个键盘，键盘在键盘中央是投影轮廓形状的键盘，主要用于标定时，在实时摄像头顶部的图形外部并将数据传递到计算机，因为激光是水平和平行的，因此没有物体遮挡摄像头无法检测到红外信号，但是如果在红外激光区域，当被遮挡物的表面被红外摄像机覆盖时，将检测到红外信号，经过一定的算法后，计算机访问摄像机发送的信号，以获取红外点图片中的坐标，然后将坐标映射到真实的键盘位置，以实现其功能。 硬件 1.选择相机镜头 同一区域的检测摄像机，“ Camera2”为视角150°，高度为“ h2”，“ Camera1”为视角90°，高度为“ h1”，以缩小项目

OpenLIDAR 足够简单的扫描激光测距仪。 基于三角剖分的方法。 使用了STM32F303 + ELIS-1024传感器。 关于它的俄语文章： : 阅读Wiki了解更多信息。 视频-安装在Roomba的激光雷达： ： 4vZgepiK1K4 我还有另一个更简单的激光雷达项目： ： 另请参阅我的TOF Lidar项目： ：

Recent developments in laser scanning technologies have provided innovative solutions for acquiring three-dimensional (3D) point clouds about road corridors and its environments. Unlike traditional field surveying, satellite imagery, and aerial photography, laser scanning systems offer unique solutions for collecting dense point clouds with millimeter accuracy and in a reasonable time. The data acquired by laser scanning systems empower modeling road geometry and delineating road design parameters such as slope, superelevation, and vertical and horizontal alignments. These geometric parameters have several geospatial applications such as road safety management. The purpose of this book is to promote the core understanding of suitable geospatial tools and techniques for modeling of road traffic accidents by the state-of-the-art artificial intelligence (AI) approaches such as neural networks (NNs) and deep learning (DL) using traffic information and road geometry delineated from laser scanning data. Data collection and management in databases play a major role in modeling and developing predictive tools. Therefore, the first two chapters of this book introduce laser scanning technology with creative explanation and graphical illustrations and review the recent methods of extracting geometric road parameters. The third and fourth chapters present an optimization of support vector machine and ensemble tree methods as well as novel hierarchical object-based methods for extracting road geometry from laser scanning point clouds. Information about historical traffic accidents and their circumstances, traffic (volume, type of vehicles), road features (grade, superelevation, curve radius, lane width, speed limit, etc.) pertains to what is observed to exist on road segments or road intersections. Soft computing models such as neural networks are advanced modeling methods that can be related to traffic and road features to the historical accidents and generates regression equations that can be used in various phases of road safety management cycle. The regression equations produced by NN can identify unsafe road segments, estimate how much safety has changed following a change in design, and quantify the effects of road geometric features and traffic information on road safety. This book aims to help graduate students, professionals, decision makers, and road planners in developing better traffic accident prediction models using advanced neural networks.

用于Unity游戏开发，激光特效，预支了10种效果，自己也可以改图片，2D Laser Beams. Unity 5.4/2017/2018 均可用！！！

激光焊接过程温度场模拟,附带说明，简洁，便于学习ansys焊接模拟

Tunable Laser Assembly

RDWorks V8 for windows

siegman 的一本激光名著，好书共分享。

Mech-Eye Laser L 结构图

Mech-Eye Laser L技术规格