Active Perception with A Monocular Camera for Multiscopic Vision
원문 초록
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.
함께 살펴볼 논문
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Multi-Label Stereo Matching for Transparent Scene Depth Estimation
Boosting Omnidirectional Stereo Matching with a Pre-trained Depth Foundation Model
FoundationStereo: Zero-Shot Stereo Matching
DEFOM-Stereo: Depth Foundation Model Based Stereo Matching
MonSter: Marry Monodepth to Stereo Unleashes Power
$S^2M^2$: Scalable Stereo Matching Model for Reliable Depth Estimation
토론
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