# Adapting Computer Vision Algorithms for Omnidirectional Video

## TL;DR

This paper reviews the challenges of applying standard computer vision algorithms to omnidirectional video and discusses strategies for adapting these algorithms to handle the unique projection and size issues.

## Contribution

It provides a high-level overview of the challenges and proposes adaptation strategies for computer vision algorithms in omnidirectional video contexts.

## Key findings

- Identifies key challenges in processing omnidirectional video.
- Summarizes adaptation strategies for existing algorithms.
- Highlights the need for specialized processing techniques.

## Abstract

Omnidirectional (360{\deg}) video has got quite popular because it provides a highly immersive viewing experience. For computer vision algorithms, it poses several challenges, like the special (equirectangular) projection commonly employed and the huge image size. In this work, we give a high-level overview of these challenges and outline strategies how to adapt computer vision algorithm for the specifics of omnidirectional video.