Jan 1, 2016 · In this study, the Lucas–Kanade template tracking algorithm in the field of computer vision is introduced to achieve displacement measurement by using existing features such as edges and texture on the structures instead of an extra target panel.

To solve this problem, we propose a generic pipeline by extending the traditional Lucas-Kanade (LK) algorithm with neural networks. The key component is how to extract the feature map, named as deep Lucas-Kanade feature map (DLKFM).

Dec 12, 2016 · We demonstrate that IC-STNs can achieve better performance than conventional STNs with less model capacity; in particular, we show superior performance in pure image alignment tasks as well as joint alignment/classification problems on real-world problems.

In-spired by the Inverse Compositional (IC) variant of the LK algorithm, we present Inverse Compositional Spatial Trans-former Networks (IC-STNs).

To relax the assumption and alleviate the drift problem, we propose CyLKs, a data-driven way of training Lucas-Kanade in an unsupervised manner. CyLKs learns a feature transformation through CNNs, transforming the input images to a feature space …

May 29, 2023 · STN在视觉学习任务中很有用，因为它将对其和分类放在同一个理论框架中。受到LK算法逆组合（Inverse Compositional，IC）变体的启发，我们提出了一种新的网络：Inverse Compositional Spatial Transformer Networks（IC-STN）。我们展示了IC-STN相比于STN可以获 …

The Lucas & Kanade (LK) algorithm is the method of choice for efficient dense image and object alignment. The approach is efficient as it at-tempts to model the connection between appearance and geometric displacement through a linear relationship that assumes independence across pixel coordinates.

Mar 29, 2016 · The Lucas & Kanade (LK) algorithm is the method of choice for efficient dense image and object alignment. The approach is efficient as it attempts to model the connection between appearance and geometric displacement through a linear relationship that assumes independence across pixel coordinates.

Sep 16, 2016 · The Lucas & Kanade (LK) algorithm is the method of choice for efficient dense image and object alignment. The approach is efficient as it attempts to model the connection between appearance and geometric displacement through a linear relationship that assumes...

Jan 1, 2016 · In this study, the Lucas–Kanade template tracking algorithm in the field of computer vision is introduced to achieve displacement measurement by using existing features such as edges and texture on the structures instead of an extra target panel.