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

机译:具有新颖的实时3D图像处理功能的高级飞行时间范围相机

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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 64×8 pixel array CMOS image sensor 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) method 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:我们提出了一种固态摄像头,该摄像头涵盖了从2 m到25 m的测量距离,并基于摄像头输出数据的三维特征,提供了新颖的实时3D图像处理算法,用于物体检测,跟踪和分类。一个64×8像素阵列CMOS图像传感器,该传感器能够通过对相机发射并由相机视场中的物体反射的NIR激光脉冲执行间接飞行时间(ToF)测量来捕获三维图像。在这里,所谓的“多重双短时积分”(MDSI)方法在抑制背景辐射和对物体场景中的反射率变化不敏感方面实现了前所未有的可靠性和鲁棒性。输出数据是常规强度值和距离值,其精度在厘米重复范围内,图像重复率最高为100 Hz。本文的主题是评估与典型道路安全相关的测试场景中相机的性能。此外,我们针对相机的输出数据流进行实时图像处理,以分割位于相机周围的物体并进行推导。可靠的位置,速度和加速度估算值。分割算法利用所有三个空间维度的位置信息以及强度值,因此与传统2D图片中的分割相比,分割效果显着提高。分割对象的位置,速度和加速度值通过3D空间中的卡尔曼滤波进行估计。该过滤器可动态适应测量条件,以处理场景数据属性的变化。通过示例场景介绍了整个处理链的流​​程和性能。

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