# mdBrief - A Fast Online Adaptable, Distorted Binary Descriptor for Real-Time Applications Using Calibrated Wide-Angle Or Fisheye Cameras

**Authors:** Steffen Urban, Stefan Hinz  
**arXiv:** [1610.07804](https://arxiv.org/abs/1610.07804)  
**Date:** 2016-10-25  
**Summary page:** https://www.summarizepaper.com/en/paper/1610.07804v1/

## Key points

- Fast binary descriptors are crucial for real-time computer vision applications like object detection, visual odometry, and SLAM.
- Traditional approaches assume images come from a perspective projection, ignoring image distortion or alternative projections like omnidirectional or fisheye cameras.
- Undistortion techniques can lead to artifacts with cameras having larger field-of-view.
- Authors Steffen Urban and Stefan Hinz propose mdBrief, a distorted binary descriptor tailored for calibrated wide-angle or fisheye cameras.
- MdBrief distorts the binary tests within the descriptor itself to adapt to different regions in an image, providing more accurate representation without introducing artifacts.

## Summary

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In the field of computer vision, fast binary descriptors play a crucial role in enabling real-time applications such as object detection, visual odometry, and SLAM. These descriptors are designed under the assumption that images and patches extracted around keypoints come from a perspective projection. However, this approach disregards image distortion or alternative projections like omnidirectional or fisheye cameras. While undistortion techniques are commonly used to correct deviations from a perfect perspective projection, they can lead to significant artifacts when dealing with cameras with larger field-of-view. To address this issue, authors Steffen Urban and Stefan Hinz propose a novel approach in their paper titled "mdBrief - A Fast Online Adaptable, Distorted Binary Descriptor for Real-Time Applications Using Calibrated Wide-Angle Or Fisheye Cameras". Instead of globally correcting distortion in acquired images, the authors introduce a distorted and masked version of the BRIEF descriptor specifically tailored for calibrated cameras. By distorting the binary tests within the descriptor itself, they are able to adapt it to different regions within an image. This innovative methodology allows for more accurate representation of features in images captured by wide-angle or fisheye cameras without introducing artifacts caused by traditional undistortion methods. The proposed mdBrief descriptor opens up new possibilities for enhancing the performance of vision-based applications operating in real-time scenarios while accommodating various types of camera projections beyond standard perspective views.