KAMERA KALİBRASYONUNDA ZEKİ OPTİMİZASYON YÖNTEMLERİNİN ETKİNLİĞİ

Bu çalışmanın amacı, literatürde Luca Lucchese’ın önerdiği kamera kalibrasyon metoduna ait model parametrelerinin optimizasyonunda zeki optimizasyon yöntemlerinin etkinliklerinin incelenmesidir. Bu algoritmalar, gerçek karmaşık dünya problemlerinin çözümünde oldukça etkili, esnek ve kolay adapte edilebilir oldukları için tercih edilmişlerdir. Seçilen algoritmalar, Yapay Arı Kolonisi (ABC), Diferansiyel Gelişim (DE), Genetik Algoritma (GA) ve Parçacık Sürü Optimizasyonu (PSO) algoritmalarıdır. Bu algoritmalardan ABC hariç diğerleri birçok gerçek dünya probleminin çözümünde kullanılmıştır. ABC algoritması yeni geliştirilmiş olduğu için literatürde Rosenbrock ve Rastrigin gibi az ve çok boyutlu bir çok temel fonksiyon üzerinde test edilmiş fakat henüz etkinliği bu tip bir kamera kalibrasyon probleminde araştırılmamıştır. Diğer zeki optimizasyon yöntemleri de bu tip bir kamera kalibrasyon problemi için ilk defa kullanılmaktadır. Algoritmaların etkinlikleri, sonuçlar Levenberg-Marguardt yöntemiyle karşılaştırılarak ortaya konulmuştur.

Anahtar Kelimeler:

Luca Lucchese Kamera Kalibrasyonu, Yapay Arı Kolonisi (ABC)

The effectiveness of intelligent optimization techniques in camera calibration

In this paper, it is aimed to examine the effectiveness of the intelligent optimization algorithms to optimize the camera parameters with respect to the calibration method introduced by Luca Lucchese (LL). The motivation of the intelligent optimization algorithms is that they are so effective, flexible and easy adaptable for the real complex problems. The selected optimization algorithms are Artificial Bee Colony (ABC), Differential Evolution (DE), Genetic Algorithm (GA) and Particle Swarm (PSO). These algorithms except ABC have been used effectively for many complex problems. ABC has recently developed and its effectiveness has not been tested for a type of the camera calibration problem. But it is highly capable of generating good solutions for many benchmark functions such as Rosenbrock and Rastrigin with both low and very high dimensions. The other artificial intelligent optimization algorithms are also the first time being used in this camera calibration problem. In order to show the effectiveness of these intelligent optimization algorithms, their results have been compared with the conventional derivative-based Levenberg-Marquardt (LM).

Keywords:

Luca Lucchese Camera Calibration, Artificial Bee Colony (ABC),

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