We propose a novel method for visual place recognition using bag of words obtained from
accelerated segment test (FAST)+ BRIEF features. For the first time, we build a vocabulary …

We propose to use binary strings as an efficient feature point descriptor, which we call
BRIEF. We show that it is highly discriminative even when using relatively few bits and can …

Binary descriptors are becoming increasingly popular as a means to compare feature points
very fast while requiring comparatively small amounts of memory. The typical approach to …

Robotic systems that can create and use visual maps in real-time have obvious advantages
in many applications, from automatic driving to mobile manipulation in the home. In this …

The efficiency and quality of a feature descriptor are critical to the user experience of many
computer vision applications. However, the existing descriptors are either too …

Autonomous driving is a key factor for future mobility. Properly perceiving the environment of
the vehicles is essential for a safe driving, which requires computing accurate geometric and …

The efficiency, robustness and distinctiveness of a feature descriptor are critical to the user
experience and scalability of a mobile Augmented Reality (AR) system. However, existing …

Higher frame-rates promise better tracking of rapid motion, but advanced real-time vision
systems rarely exceed the standard 10–60Hz range, arguing that the computation required …

We present a method for detecting revisited places in a image sequence in real time by
using efficient features. We introduce three important novelties to the bag-of-words plus …

We present a method that unifies tracking and video content recognition with applications to
Mobile Augmented Reality (MAR). We introduce the Radial Gradient Transform (RGT) and …