3-D shape recognition by active vision-without camera velocity information
3-D shape recognition by active vision-without camera velocity information
复制标题
通过主动视觉进行 3D 形状识别 - 无需相机速度信息
DOI：
10.1109/icpr.1992.201535
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发表时间：
1992
期刊：
影响因子：
--
通讯作者：
K. Deguchi
中科院分区：
文献类型：
--
作者：
K. Kinoshita;K. Deguchi
提出了一种在不知道摄像机运动参数的情况下识别物体三维形状的主动视觉方法。运动参数的计算从光流和物体点的深度，其3-D形状是已知的。然后，使用这些计算的运动参数和光流，未知点的三维位置被重建，这反过来，将被用作下一帧图像中的已知点。这些过程被迭代用于图像序列以识别3D场景。在该方法中，通过两种方法克服量化误差的影响。利用大量的点集计算摄像机运动参数，补偿了摄像机运动参数的误差。然后，卡尔曼滤波方法应用于图像序列，以减少每个未知点的三维位置误差。<<ETX>>
Proposes a new method of active vision which recognizes the 3-D shape of objects without knowing camera motion parameters. The motion parameters are calculated from the optical flows and the depth of object points whose 3-D shape is already known. Then, using these calculated motion parameters and the optical flows, the 3-D position of unknown points are reconstructed, which, in turn, will be used as the known points in the next frame of image. These processes are iterated for a sequence of images to recognize the 3-D scene. In this method, the effects of quantization errors are overcome by two approaches. The errors of camera motion parameters are compensated by using a large number of points to calculate them. Then, the Kalman filtering method is applied to the sequence of images to reduce the 3-D position errors of each unknown point.<<ETX>>