STN-Homography: estimate homography parameters directly
In this paper, we introduce the STN-Homography model to directly estimate the homography matrix between image pair. Different most CNN-based homography estimation methods which use an alternative 4-point homography parameterization, we use prove that, after coordinate normalization, the variance of elements of coordinate normalized $3\times3$ homography matrix is very small and suitable to be regressed well with CNN. Based on proposed STN-Homography, we use a hierarchical architecture which stacks several STN-Homography models and successively reduce the estimation error. Effectiveness of the proposed method is shown through experiments on MSCOCO dataset, in which it significantly outperforms the state-of-the-art. The average processing time of our hierarchical STN-Homography with 1 stage is only 4.87 ms on the GPU, and the processing time for hierarchical STN-Homography with 3 stages is 17.85 ms. The code will soon be open sourced.
Code (0)
등록된 구현이 없습니다.
Tasks
GPUHomography EstimationSimilar Papers 제목 키워드 기반
Deep Image Homography Estimation
We present a deep convolutional neural network for estimating the relative homography between a pair of images. Our feed-forward network has 10 layers, takes two stacked grayscale images as input, and produces an 8 degre…
Homography EstimationPrecise Aerial Image Matching based on Deep Homography Estimation
Aerial image registration or matching is a geometric process of aligning two aerial images captured in different environments. Estimating the precise transformation parameters is hindered by various environments such as …
Homography EstimationImage RegistrationRoad-aware Monocular Structure from Motion and Homography Estimation
Structure from motion (SFM) and ground plane homography estimation are critical to autonomous driving and other robotics applications. Recently, much progress has been made in using deep neural networks for SFM and homog…
Autonomous DrivingHomography EstimationRoad SegmentationHSolo: Homography from a single affine aware correspondence
The performance of existing robust homography estimation algorithms is highly dependent on the inlier rate of feature point correspondences. In this paper, we present a novel procedure for homography estimation that is p…
Homography EstimationWarped Convolutional Networks: Bridge Homography to sl(3) algebra by Group Convolution
Homography has an essential relationship with the special linear group and the embedding Lie algebra structure. Although the Lie algebra representation is elegant, few researchers have established the connection between …
Homography EstimationObject Tracking