This dissertation contributes to an in-depth analysis of the SIFT method. SIFT is the most
popular and the first efficient image comparison model. SIFT is also the first method to …

In this paper, we propose a new approach for sub-pixel co-registration based on Fourier
phase correlation combined with the Harris detector. Due to the limitation of the standard …

Most computer vision application rely on algorithms finding local correspondences between
different images. These algorithms detect and compare stable local invariant descriptors …

We address the problem of cross-domain image localization, ie, the ability of estimating the
pose of a landmark from visual content acquired under various conditions, such as old …

Feature detection is a basic issue in computer vision, and the illumination robustness of the
detector is an important evaluation indicator. However, no indicators that can directly and …

Most computer vision application rely on algorithms finding local correspondences between
different images. These algorithms detect and compare stable local invariant descriptors …

Localization has long been a key research topic in computer science due to its applications
in autonomous vehicles, surveillance, security, and indoor positioning systems. Visual Place …

Since local feature detection has been one of the most active research areas in computer
vision during the last decade and has found wide range of applications (such as matching …

Most computer vision applications rely on algorithms finding local correspondences
between different images. These algorithms detect and compare stable local invariant …

Visual Place Recognition (VPR) enables autonomous systems to localize themselves within
their environment using image information, a crucial component of robotic navigation. The …