加拿大代写-三角剖分技术的计算距离研究了三维嵌入式视觉系统中的三角剖分方法，并将其应用于自动驾驶车辆的深度分析或深度信息处理。三维嵌入式视觉相机采用的技术有激光扫描三角测量、结构光三角测量以及飞行时间成像。因此，通过飞行时间信息来检测障碍物的距离或距离(Appiah & Bandaru, 2011)。不同的视觉系统用于三角测量。
Triangulation is studied in the 3D embedded vision systems, which are used for the depth analyses or the depth information in the autonomous vehicles. The technologies that are adopted in the 3D embedded vision cameras are the laser scan triangulation, and structured light and triangulation, as well as time of flight imaging. Therefore, the distance or the range of the obstacle is detected through the time-of-flight information (Appiah & Bandaru, 2011). Different kinds of vision systems are used for triangulation.
Passive triangulation is used for measuring distance for more than a decade. “The stereo imaging system use the two aligned and calibrated cameras and finds the correspondences between points seen by one camera and the same ones seen by the other camera” (Li, 2017, p. 18). Later, the 3D location of the points is calculated with the baseline separation occurring between the cameras and correspondences between the cameras. Such cameras do not have the requirement of the built in light source. Therefore, this technology of 3D vision is called as passive triangulation. The passive triangulation principle can be explained as:
The depth is considered as Z and the centres of projection are considered as Ot and Or. The principle points of the two images are considered as Ct and Cr. The depth of the point W is considered as inversely ƛproportional to disparity occurring between the stereo views. Disparity is defined as d = x1- x2. The known baseline separation is presented as B, thus it can be derived as
Z /B = f/d = f /(xl − xr) ⇒ Z = T · f /(xl − xr) .
Due to the additional depth information, the triangulation of the stereoscopic system is considered as more reliable for detection of the objects. The stereo imagies are dense and allow to make the stereo front viwe camera as more accurate. Therefore, the vision based sensors are very helpful in indetifying the pedestrians, traffi signs and on road traffic scenes. The main technique that is used by these sensors is image processing and pattern recognition (Musleh et al., 2010). The active triangulation requires the light source for illuminating the scene. However, something that is similar like passive triangulation is that the 3D object information is first perceived and then analysed.