---
title: "Groupwise Registration of Aerial Images"
authors:
  - "Ognjen Arandjelovic"
  - "Duc-Son Pham"
  - "Svetha Venkatesh"
doi: ""
url: "https://ijcai.org/proceedings/2015/302"
pdf: "https://ijcai.org/proceedings/2015/0302.pdf"
venue: "Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence"
year: 2015
pages: "2133-2138"
track: "Main Track"
keywords:
---

# Groupwise Registration of Aerial Images

Ognjen Arandjelovic, Duc-Son Pham, Svetha Venkatesh

*Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence*, pages 2133-2138.

## Abstract

This paper addresses the task of time separated aerial image registration. The ability to solve this problem accurately and reliably is important for a variety of subsequent image understanding applications. The principal challenge lies in the extent and nature of transient appearance variation that a land area can undergo, such as that caused by the change in illumination conditions, seasonal variations, or the occlusion by non-persistent objects (people, cars). Our work introduces several novelties: (i) unlike all previous work on aerial image registration, we approach the problem using a set-based paradigm; (ii) we show how local, pair-wise constraints can be used to enforce a globally good registration using a constraints graph structure; (iii) we show how a simple holistic representation derived from raw aerial images can be used as a basic building block of the constraints graph in a manner which achieves both high registration accuracy and speed. We demonstrate: (i) that the proposed method outperforms the state-of-the-art for pair-wise registration already, achieving greater accuracy and reliability, while at the same time reducing the computational cost of the task; and (ii) that the increase in the number of available images in a set consistently reduces the average registration error.