6 accepted papers
Satellite imagery has traditionally been used to collect crop statistics, but its low resolution and registration accuracy limit agricultural analytics to plant stand levels and large areas. Precision agriculture seeks analytic tools at near single plant level, and this work explores how to improve…
Place recognition is an essential capability for robotic autonomy. While ground robots observe the world from generally similar viewpoints over repeated visits, other robots, such as small aircraft, experience far more different viewpoints, requiring place recognition for images captured from very w
Research on learning suitable feature descriptors for Computer Vision has recently shifted to deep learning where the biggest challenge lies with the formulation of appropriate loss functions, especially since the descriptors to be learned are not known at training time. While approaches such as Sia…
With a large body of literature dedicated to ego-motion estimation and perception of a robot's workspace, the robotics community has seen some impressive advances in self-localization and mapping, however, we are still far from general applicability of such approaches in real scenarios. Driven by th
The booming interest in Unmanned Aerial Vehicles (UAV s) is fed by their potentially great impact, however progress is hindered by their limited perception capabilities. While vision-based odometry was shown to run successfully onboard UAV s, loop-closure detection to correct for drift or to recover…
Recently, image representations derived from Convolutional Neural Networks (CNNs) have been demonstrated to achieve impressive performance on a wide variety of tasks, including place recognition. In this paper, we take a step deeper into the internal structure of CNNs and propose novel CNN-based ima…