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Advanced time-of-flight range camera with novel real-time 3D image processing

机译:具有新型实时3D图像处理的先进的飞行时间摄像机

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We present a solid state range camera covering measuring distances from 2 m to 25 m and novel real-time 3D image processing algorithms for object detection, tracking and classification based on the three-dimensional features of the camera's output data.The technology is based on a 64x8 pixel array CMOS image sensor1 which is capable of capturing three-dimensional images by executing indirect time-of-flight (ToF) measurement of NIR laser pulses emitted by the camera and reflected by the objects in the cameras field of view. Here the so-called "multiple double short time integration" (MDSI) method2 enables unprecedented reliability and robustness with respect to suppression of background irradiance and insensitiveness to reflectivity variations in the object scene. Output data are conventional intensity values and distance values with accuracies in the centimeter range at image repetition rates up to 100 Hz. An evaluation of the camera's performance in typical road safety related test scenarios is subject of this paper.Furthermore we introduce real-time image processing of the output data stream of the camera aiming at the segmentation of objects being located in the camera's surrounding and the derivation of reliable position, speed and acceleration estimates. The segmentation algorithm utilizes the position information of all three spatial dimensions as well as the intensity values and thus yields significant segmentation improvement compared to segmentation in conventional 2D pictures. Position, velocity and acceleration values of the segmented objects are estimated by means of Kalman filtering in 3D space. The filter is dynamically adapting to the measurement conditions to take care of changes of the scene data properties. Flow and performance of the whole processing chain are presented by means of example scenes.
机译:我们介绍了一个固态范围相机,覆盖测量距离为2米到25 m的距离和新的实时3D图像处理算法,用于基于相机输出数据的三维特征的对象检测,跟踪和分类。技术基于一种64x8像素阵列CMOS图像传感器,其能够通过执行由相机发出的NIR激光脉冲的间接飞行时间(TOF)测量来捕获三维图像,并由相机视野中的物体反射。这里所谓的“多个双短时间集成”(MDSI)方法2具有关于抑制背景辐照度和对象场景中的反射率变化的抑制和不敏感的稳健性。输出数据是常规强度值和距离值,在厘米范围内的厘米范围,图像重复率高达100Hz。在典型的道路安全相关测试场景中对相机性能的评估是本文的主题。许多我们介绍了旨在对位于相机周围的物体的分割的相机输出数据流的实时图像处理可靠的位置,速度和加速度估算。分割算法利用所有三个空间尺寸的位置信息以及强度值,从而产生与传统2D图片中的分段相比的显着分割改进。通过3D空间中的卡尔曼滤波估计分段对象的位置,速度和加速度值。过滤器在动态地调整到测量条件,以处理场景数据属性的变化。通过示例场景呈现整个处理链的流​​量和性能。

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