论文标题
用单眼相机进行多识别视觉的主动感知
Active Perception with A Monocular Camera for Multiscopic Vision
论文作者
论文摘要
我们设计了一个多脑视觉系统，该系统利用低成本的单眼RGB摄像头来获取机器人应用的准确深度估计。与以无约束的相机姿势捕获的图像的多视图立体声不同，建议的系统积极地控制一个具有安装摄像头的机器人臂，以捕获具有相同视差的水平或垂直对齐位置中的一系列图像。在此系统中，我们将参考图像和周围图像之间立体声匹配的成本量结合在一起，以形成融合的成本量，对异常值稳健。 Middlebury数据集和实际机器人实验的实验表明，我们获得的差异图比两框立体声匹配更准确：在我们的实验中，平均绝对误差降低了50.2％。
We design a multiscopic vision system that utilizes a low-cost monocular RGB camera to acquire accurate depth estimation for robotic applications. Unlike multi-view stereo with images captured at unconstrained camera poses, the proposed system actively controls a robot arm with a mounted camera to capture a sequence of images in horizontally or vertically aligned positions with the same parallax. In this system, we combine the cost volumes for stereo matching between the reference image and the surrounding images to form a fused cost volume that is robust to outliers. Experiments on the Middlebury dataset and real robot experiments show that our obtained disparity maps are more accurate than two-frame stereo matching: the average absolute error is reduced by 50.2% in our experiments.
