The spatial distribution of feature points is known to affect the accuracy of homography estimation and hence the effectiveness of applications such as image stitching. This paper explores the use of spatial statistics as a metric for feature coverage, the distribution of features in an image. The coverages achieved by several feature detectors are compared and it is shown that detectors with higher coverages achieve better results in an image-stitching application. It is found that that SFOP is the most effective detector considered. © 2012 Institute of Telecommunica
Image stitching requires accurate matching of visual features to achieve good alignment. However, f...
Statistical patch-based observation (SPBO) is built specifically for obtaining good tracking observa...
In many algorithms the registration of image pairs is done by feature point matching. After the feat...
Enlarged images can be obtained by various methods. Stitching is one of the efficient methods. It ca...
Image stitching is a method of producing a wider field of view by combining several overlapping imag...
When matching images for applications such as mosaicking and homography estimation, the distribution...
In this project work, the objective is to implement and design an algorithm of image stitching const...
The main purpose of this paper is a comparison of the algorithms for computing homography. It compar...
The goal of homography estimation is to find global transformation between two images of the same sc...
Panoramic images were first created in the middle of the 19th century and it became popular in moder...
We present a large scale benchmark for the evaluation of local feature detectors. Our key innovation...
Panoramic stitching is an image processing technique that involves combining two or more images with...
Repeatability is widely used as an indicator of the performance of an image feature detector but, al...
In this paper the problem of fully automated panoramic image stitching for 2D image is introduced. I...
This paper presents the methods of extracting distinctive invariant features from the set of images....
Image stitching requires accurate matching of visual features to achieve good alignment. However, f...
Statistical patch-based observation (SPBO) is built specifically for obtaining good tracking observa...
In many algorithms the registration of image pairs is done by feature point matching. After the feat...
Enlarged images can be obtained by various methods. Stitching is one of the efficient methods. It ca...
Image stitching is a method of producing a wider field of view by combining several overlapping imag...
When matching images for applications such as mosaicking and homography estimation, the distribution...
In this project work, the objective is to implement and design an algorithm of image stitching const...
The main purpose of this paper is a comparison of the algorithms for computing homography. It compar...
The goal of homography estimation is to find global transformation between two images of the same sc...
Panoramic images were first created in the middle of the 19th century and it became popular in moder...
We present a large scale benchmark for the evaluation of local feature detectors. Our key innovation...
Panoramic stitching is an image processing technique that involves combining two or more images with...
Repeatability is widely used as an indicator of the performance of an image feature detector but, al...
In this paper the problem of fully automated panoramic image stitching for 2D image is introduced. I...
This paper presents the methods of extracting distinctive invariant features from the set of images....
Image stitching requires accurate matching of visual features to achieve good alignment. However, f...
Statistical patch-based observation (SPBO) is built specifically for obtaining good tracking observa...
In many algorithms the registration of image pairs is done by feature point matching. After the feat...