A review of multimodal image matching: Methods and applications
X Jiang, J Ma, G **: Using Kinect-style depth cameras for dense 3D modeling of indoor environments
RGB-D cameras (such as the Microsoft Kinect) are novel sensing systems that capture RGB
images along with per-pixel depth information. In this paper we investigate how such …
images along with per-pixel depth information. In this paper we investigate how such …
GMS: Grid-based motion statistics for fast, ultra-robust feature correspondence
Incorporating smoothness constraints into feature matching is known to enable ultra-robust
matching. However, such formulations are both complex and slow, making them unsuitable …
matching. However, such formulations are both complex and slow, making them unsuitable …
Learning to find good correspondences
We develop a deep architecture to learn to find good correspondences for wide-baseline
stereo. Given a set of putative sparse matches and the camera intrinsics, we train our …
stereo. Given a set of putative sparse matches and the camera intrinsics, we train our …
Efficient RANSAC for point‐cloud shape detection
R Schnabel, R Wahl, R Klein - Computer graphics forum, 2007 - Wiley Online Library
In this paper we present an automatic algorithm to detect basic shapes in unorganized point
clouds. The algorithm decomposes the point cloud into a concise, hybrid structure of …
clouds. The algorithm decomposes the point cloud into a concise, hybrid structure of …
Image matching across wide baselines: From paper to practice
We introduce a comprehensive benchmark for local features and robust estimation
algorithms, focusing on the downstream task—the accuracy of the reconstructed camera …
algorithms, focusing on the downstream task—the accuracy of the reconstructed camera …