Odometry is crucial for robot navigation, particularly in situations where global positioning
methods like global positioning system are unavailable. The main goal of odometry is to …

Simultaneous localization and mapping (SLAM) is an active research topic in machine
vision and robotics. It has various applications in many different fields such as mobile robots …

This paper tackles the problem of Cross-view Video-based camera Localization (CVL). The
task is to localize a query camera by leveraging information from its past observations, ie, a …

Hierarchical concepts have proven useful in many classical and learning-based optical flow
methods regarding both accuracy and robustness. In this paper we show that such concepts …

Visual odometry (VO) is one of the promising techniques that estimates pose using the
camera and does not necessarily require other sensor aiding. With increasing automation …

Visual odometry and visual simultaneous localization and mapping aid in tracking the
position of a camera and mapping the surroundings using images. It is an important part of …

The digitization of surgical operating rooms (OR) has gained significant traction in the
scientific and medical communities. However, existing deep-learning methods for operating …

In this work, we investigate loop closure detection through a deep reinforcement learning
approach. The loop closure detection problem correctly identifies a location or area a robot …

Visual odometry is the process of estimating the motion between two consecutive images.
Traditional visual odometry algorithms require the careful fabrication of state-of-the-art …

This paper presents a novel data-driven navigation system to navigate an Unmanned
Vehicle (UV) in GPS-denied, feature-deficient environments such as tunnels, or mines. The …