How Far Can You Get By Combining Change Detection Algorithms?

TL;DR

This paper introduces IUTIS, a genetic programming-based method to combine change detection algorithms, improving performance and efficiency for real-time applications by leveraging their strengths and compensating for weaknesses.

Contribution

The paper presents a novel combination strategy, IUTIS, that effectively integrates multiple change detection algorithms using genetic programming, enhancing accuracy and computational efficiency.

Findings

Comparable results to state-of-the-art algorithms

Achieves real-time computational efficiency

Balances performance and efficiency in change detection

Abstract

Given the existence of many change detection algorithms, each with its own peculiarities and strengths, we propose a combination strategy, that we termed IUTIS (In Unity There Is Strength), based on a genetic Programming framework. This combination strategy is aimed at leveraging the strengths of the algorithms and compensate for their weakness. In this paper we show our findings in applying the proposed strategy in two different scenarios. The first scenario is purely performance-based. The second scenario performance and efficiency must be balanced. Results demonstrate that starting from simple algorithms we can achieve comparable results with respect to more complex state-of-the-art change detection algorithms, while keeping the computational complexity affordable for real-time applications.